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Four Ways Advanced Analytics Drives Business Forward

2020 was an unprecedented year for shifting businesses online. Technology, never quite in the background, arrived center stage to help drive transformation in a variety of industries. Many businesses were forced to change their processes, how they interacted with their employees, customers, and with each other. One of these major shifts was in Advanced Analytics and Insight. Stemming from a Marketing perspective which had specific deliverables of demographics, location, and consumer histories, advancements found a place in working with unstructured Data. Working in tandem with these new analytical insights, artificial intelligence brought learning, problem-solving, planning, and other naturally human behaviors to life. This includes in the creative fields, not just in traditional industries like Finance or Retail.  In a study conducted by Forrester on behalf of Intel, though most businesses know Analytics can drive their business forward, less than half are taking advantage of these transformational technologies. Below are a few ways Advanced Analytics can drive business forward. 1. Decision Science and the CDO Roles Will Grow In a seemingly counterintuitive measure, while most businesses were cutting back in IT, Data and Analytics budgets were expanded. As the Chief Data Officer and Decision Science roles increase in importance, businesses who know the value of their Data can derive actionable insights and business decisions from these executive level communicators. 2. Access to a variety of Data Sources Will Help to Streamline Business Operations With most businesses operating strictly online or in a hybrid ecosystem, optimization of processes is key. In the ever-changing market systems, buyer behaviors and the consumer journey will increase dependency on Data and Analytics as businesses seek to meet consumer demand. Offering bespoke solutions and coordinating such Data sources as chatbots and call centers, businesses will have the opportunity to create a seamless system as they adopt and implement technologies such as Advanced Analytics and AI. In the right mindset, these practices can also drive partnerships within their ecosystems from Data Science to technology vendors with AI capabilities.  3. Sharpening Focus on Measurable Projects to Increase ROI Rather than rely on third parties, Data will become part of the business offering value in their operations. It will drive how they operate, deliver, and understand the needs of their consumer. Owning and managing their own Data will provide unique insights they may not have been aware of before. Sharpening their focus to get a good return on their analytics investment, businesses will broaden their ecosystem. Seeing the bigger picture, businesses will also want to access more specific insights that drive actionable answers to their questions. 4. Machine Learning, NLP, and Domain Expertise Can Help Scale Data Modelling As AI, Advanced Analytics, NLP, and Machine Learning platforms come into full swing and in combination, new Data Modelling opportunities can increase insight. Automated processes of Data classifications will drive scale increasing both the amount of Data and a granular level of detail to be extracted.  The specialization of these Data platforms will only grow in importance. In our always-on, always on demand world, the need for Advanced Analytics professionals and a variety of posts in the Data profession, businesses will expect strong domain knowledge. They’ll be looking for professionals and platforms which can help them understand specific use cases. Rather than just simple demographics and birds-eye views of their consumers, they’ll want to drill down to not only what they can provide now in terms of goods and services, but anticipate what consumers will want and need for the future. In the last year, we’ve absorbed a lot of information, and have struggled to distill it in actionable insights. But, if you’re interested in Marketing and Insight, and would like to shift into Advanced Analytics and Insight, we may have a role for you. Not your bag, but interested in Life Sciences, Decision Science, Machine Learning, or Robotics just to name a few, Harnham may have a role for you. Check out our current vacancies or contact one of our expert consultants to learn more.  For our West Coast Team, contact us at (415) 614 - 4999 or send an email to sanfraninfo@harnham.com.  For our Mid-West and East Coast teams contact us at (212) 796-6070 or send an email to newyorkinfo@harnham.com.  

Back To Basics In The Business Of Data Science

Though COVID-19 and the US Election still dominates the news, there’s a lot going in the world of Data Science, too. 2020 ramped up efforts in the healthcare industry to combat the pandemic. Cybersecurity is entering a renaissance of sorts as we tackle the misinformation age, but there’s some fun stuff, too. Here a few Data Science trends finding foundation and leverage in 2021. Businesses Kick Data Science into High Gear To stay viable, businesses are kicking their Data Strategy into high gear. From the top down, there will be an estimated increase of Chief Data Scientists to help businesses make critical business decisions from e-commerce to SaaS. Trajectory of Data Analysts Upskilling to Data Scientist  Once relegated to sampling bits of data and leaving others to break it down into workflow, Data Scientists could see a boost of responsibility. The demand for soft skills, upskilling, and cross-training could reduce the need to have Machine Learning and Data Engineers process empowering the Data Scientists to do more. Breaking the Mold With businesses and education moved online, businesses will be challenged to keep employees engaged. Training and education are now available to employees and would-be Data Scientists at home for on-the-job training as they face new technologies being developed, use new tools, and lessened demand on the college degree, but the experience in applying what’s been learned. Machine Learning Gets Smarter AI and Machine Leaning applications will focus on charting algorithms to understand cause-and-effect. But it won’t happen overnight. Teaching and testing machines is intense and time consuming. These technologies might present probability, but can’t determine definites. Yet.  Applying Machine Learning strategies to business problems through systems will focus businesses on finding solutions rather than focusing on building products that aren’t in their wheelhouse. Adding neuroscience and computational neuroscience into the mix for Machine Learning will see these fields grow. Ultimately, Machine Learning and AI are estimated to be the final piece in the puzzle when it comes to Data Science strategies for a variety of industries.  Back to Basics As everyone gets organized in their new ways of doing business, Data Scientists are getting back to basics. Their solving big problems with better tools, technologies, and open-source information now available. The push for open access scientific and medical journals along with the global team environment offers a variety of ways in which Data Scientists can come together to focus on problems more efficiently than anyone else. In other news, projects such as the new James Webb Telescope, the open access drive for scientific and medical journals, and the latest space race information, Data Scientists have been busy getting these projects off the ground as well. Though 2020 took us by surprise in so many ways, we took what we had and ran with it. So, as we enter 2021, we’re on a unique footing from Machine Learning and AI to Data Science with the added boost of nuero-and computational science to employ every tool at our disposal. Businesses have ramped up their efforts and are empowering the professionals in the Data Strategy teams to help them make critical business decisions with an eye toward the future. Data Scientists are getting back to basics while leveraging their skillsets from open access, online education sources, and on-the-job training to solve the big problems we face. And of course, while we have our eyes on the sky when it comes to space exploration this year and our feet on the ground as we work to vaccinate populations against COVID-19, and Chief Data Scientists split their focus to improve business bottom lines, we know demand will remain high for those in the Data industry. If you’re interested in Data & Analytics, Harnham may have a role for you. Check out our current vacancies or contact one of our expert consultants to learn more.  For our West Coast Team, contact us at (415) 614 - 4999 or send an email to sanfraninfo@harnham.com.  For our Mid-West and East Coast teams contact us at (212) 796-6070 or send an email to newyorkinfo@harnham.com.

Could Mobile Gaming Help Us Solve Real World Problems?

From Alexandra Ocasio-Cortez and Ilhan Omar’s Twitch play Among Us to Fortnite helping kids get into college, the mobile gaming industry has leapt into the new decade with gusto. It doesn’t hurt to have a few well-known names behind it, too. But it’s what AOC and Oman accomplished -normalcy - that begs the question. Could mobile gaming help us solve real world problems?  A Cultural Beginning             Cultural institutions, such as museums, have had a rough go of it this year. But innovation, creativity, and collaboration have come together to offer opportunities to get a bird’s eye view of the art world. Whether you play Occupy White Walls to create your own gallery bring real art into your gaming world through the Getty Museum and Nintendo’s Animal Crossing collaboration. Just a few ways these could be jumping off points to discussion for problem-solving include: Opportunities abound to host audiences from around the world without a head count capA chat function to discuss what you see, what you like, what you don’t, and what you’d like to seeCultural institutions become more open allowing anyone and everyone into its virtual wallsPerhaps even simulations and to imagine what-if scenarios for the rest of usGames could host exhibitions such as the Monterey Bay Aquarium of California who’s partnered with Animal Crossing and a fossil expert form the Field Museum in Chicago who hosts virtual tours through Twitch Games give us the opportunity to imagine what’s possible. And these games are bringing real life events and activities straight to your fingertips in mobile gaming. Ad-Tech and Analytics are In the Game Since social distancing has become the norm, gaming has exploded. Once all the numbers are in, mobile game downloads are expected to see a nearly 40% increase in 2020 from 2019. No business who sees the potential here is standing by, the least of which is advertising. If you remember cable TV or maybe still have one, the free channels were often supported by commercials. In some television shows, products were given strategic placement. Okay, so it’s probably still happening today, but now we’re used to it. Skip ahead a few generations. Hello, Ready Player One fans, and advertisers have a new platform. Or at least, they’re working on it. There are still a few kinks to work out. Some game developers are designing games to help allow advertisers to fit seamlessly into games.  The audience of one engagement of TV has moved to a community engagement of many in the gaming world. Over two and half billion people are gamers across demographics of age and location. Social media still has the highest ad buys from television, but gaming is quickly catching up. As advertisers and businesses get in the game, it’s estimated there will be a monumental shift in the collective. Games have always served as a device to teach. Chess and checkers teach strategy. Monopoly teaches business and banking. Life teaches us to follow different paths and see what happens (not so different from Second Life). So, what could games teach us now with its ever increasing role in bringing groups together for engagement, community, and discussion? What role will you play in the coming year? If you’re interested in Data & Analytics, Harnham may have a role for you. Check out our current vacancies or get in touch with one of our expert consultants to learn more.  For our West Coast Team, contact us at (415) 614 - 4999 or send an email to sanfraninfo@harnham.com.  For our Mid-West and East Coast teams contact us at (212) 796-6070 or send an email to newyorkinfo@harnham.com.  

Business Intelligence Is About Asking The Right Questions

You’ve dotted all the ‘Is’, crossed all the ‘Ts’. You’ve ensured your business priorities were aligned with your mission and objectives. But, how can you know if you’re on the right path, especially in light of today’s uncertainties. Your crystal ball may be in the cloud, but to find its clarity, you have to be asking the right questions. Below are three questions to consider moving forward. 1. How Collaborative Are We? As businesses shift online and teams expand globally, collaborative business intelligence streamlines decision-making. A combination of BI tools, software, and social technologies to inform, engage, analyze, and form insights of what customers want and need. This form of collaboration takes decision-making out of its siloes. Not unlike the Socratic method, collaborative business intelligence solves problems through shared information to find common ground. Using business intelligence software to provide opportunities for predictive modeling, visual analysis of data and business metrics, businesses analysts can interpret and inform, in a more efficient streamlined process. 2. How Secure is Our Data? Whether big business, small business, or medium business, no one is immune to cyberattacks. The ever- increasing rise of these attacks pinpoints just how important keeping data secure is for all businesses. Breaches cause not only monetary loss, but ultimately, consumer trust leading to more loss. The importance of Data security cannot be overstated.  Now that a majority of businesses are making flexible and remote work options available, it’s imperative businesses work to keep data secure. Consumers today are much more concerned today about how and why their Data is used, and many may decline to offer it, not wanting to put themselves at risk of a possible cyberattack.  3. What’s the Best Platform to Drive Actionable Insights from Our Analytics? Much like the trend of collaborative BI, businesses are focused on combining business processes and workflows into one platform, so everyone has access to the same Data. It’s within these platforms, that businesses cannot only determine what action to take and implement those actions all in one place. Platforms become the hub of the wheel and the spokes are analytics of a particular industry, business, or department in which insights can be implemented. Some platforms on the move include Sisense and Sharepoint. Google Analytics Intelligence (GAI) might be the most well-known especially if you’re just getting started asking the right questions for your business.  If you want insight into the state of your business, know any major consumer traffic changes, or want to know the probable conversion rate of web browsers to customers, GAI can help you get those answers. Because it uses machine learning to help, it’s important to know not necessarily what questions to ask, but how to ask them. How to Ask a Computer the Right Questions If you’ve been working in a collaborative BI team and asking each other questions based on the data you’ve collected, it may be a bit of a mindset shift for asking questions of a computer. So, how you phrase your question, what you want to know, and how you ask may require a bit of thought to find the answers you’re looking for. Below are a few guidelines to consider when posing the questions.Follow the TrendIf you want to know what’s trending in your business, you might ask: How many products were sold last week?How many customers did I have today?Where are my customers located?What time were the most customers shopping?  Which is Best? When you want to know what product is selling the most and through which means. Follow the performance. These questions might include: Which channel converted the most customers?Which product sold the most? Which product sold the least?Which hour was best for customer traffic? Compare and Contrast These are questions or commands that enable you to compare two sets of data side by side, such as how your business performed week to week, day to day, or year to year. While most questions begin with ‘which’ or ‘how’, the compare and contrast questions can get a bit more complex. In these questions, you begin with what you want to know such as conversion rate, revenue shares, traffic, or trend.  As this year comes to a close, what questions will you ask of yourself? Are you ready for a change? A new role? If you’re a business, what questions will you ask to move your company forward in the new year? If you’re interested in Big Data & Analytics, we may have a role for you. Check out our current opportunities or contact one of our expert consultants to learn more.  For our West Coast Team, contact us at (415) 614 - 4999 or send an email to sanfraninfo@harnham.com.  For our Mid-West and East Coast teams contact us at (212) 796-6070 or send an email to newyorkinfo@harnham.com.  

Computer Vision Offers Safety and Security in Surprising Industries

At a Yale University speech several years ago, Peter Thiel, the founder of PayPal joked, “We wanted flying cars, instead we got 140-characters”. Well, flying cars are still in the future, and so are self-driving cars. Yet, some autonomous vehicles have found homes in the most unlikely of industries.  The rules and regulations which keep our roads safe are also hindering our ability to realize self-driving cars. Yet, safety measures abound ready to ‘plug-and-play’ the safe handling of you in the driver’s seat and those with whom you share the road. Hands off the steering wheel, of course. Three Ways Computer Vision is Preparing for Driverless Cars 3-D Mapping for RealTime Learning – much like your backing camera on your latest automobile, car cameras can also record live footage to map their environment. From this Data, autonomous vehicles can spot obstacles or determine alternate paths.Sensing Obstacles and Objects – using sensors to determine what the obstacle or object in the road is – whether it’s pedestrians, other vehicles, or even something as simple as a loose bag or cardboard flap. If it’s something you’d have to drive around to avoid hitting, shouldn’t your car know this, too?Gathering Detailed Data – can help your self-driving vehicle identify traffic lights, road conditions, and congestion. Each of these elements are steps to a more reliable experience, once driverless cars come on the scene. In the meantime, there’s an old industry bringing machine and human together like never before. Building for the future is employing robotics, AI, and Computer Vision technologies for seamless integration. Building Technology: Computer Vision Meets Construction Sites It’s backbreaking work to move dirt from one place to another, but if you’re going to build, it’s the first thing to be done. It’s also the most repetitious and mundane. Enter autonomous heavy equipment. These machines prepare the sites for the human crews who will come in later to do the building itself. Before panic sets in that robots are replacing people, understand that people can still move faster than these large machines. The idea behind automating processes is to ensure projects remain on schedule using consistent, reliable resources; man and machine working together. Yet, there is one place where man shines and machine does not. Controlled chaos and changing conditions. The Computer Vision elements employed here can help systems to recognize things such basics as utility lines and variances such as historical artifacts. Finding something like an archeological site or historical artifact can stall or stop a project. But whether the site’s on track to finish on schedule or a glitch throws a curveball into the schedule, the site still needs to be protected. Who better than a drone? Safety First – Construction Site to Driver’s Seat Autonomous vehicles whether on the road or in the sky offer a unique view of their environment. Just as driverless cars are employing 3D mapping and object identification, drones are being used to help navigate and manage construction-size projects. Below are a few ways they’re making waves: Predictive Modelling using Computer Vision - predict how much on-site material may be needed.Put together prefabricated partsTrack progress and watch for things like structural issues, number of trucks entering a site, even if teams are following best practices. Though driverless cars are still future forward ideas, driverless trucks, and other autonomous heavy equipment are in the driver’s seat. Making the idea of working with machines exciting to the professionals in the industry is one way to make the idea more palatable. The move to intelligent, more reliable systems to keep projects and people on track, on budget, safe, and to ultimately solve a problem offers bold solutions for the future. If you’re interested in Big Data, Analytics, Life Sciences, and more opportunities in the Data professional’s industry, Harnham may have a role for you. Check out our current vacancies or get in touch with one of our expert consultants to learn more: For our West Coast Team, contact us at (415) 614 - 4999 or send an email to sanfraninfo@harnham.com.   For our Mid-West and East Coast teams contact us at (212) 796-6070 or send an email to newyorkinfo@harnham.com.  

Making It As A Woman In Data Science: An Interview with Ashley Holmes

Meet Ashley Holmes. Senior Data Scientist for a firm working to improve healthcare. Or rather, the healthcare system.                   It’s been an unusual year by all accounts. Most jobs have moved online for the foreseeable future, yet jobless rates climb. Everyone is learning to pivot and accelerating their focus and skillsets. It’s also a time to evaluate where you are in your career and where you want to go. So, from time to time, we find it’s best to hear some stories directly from those in the field.  Ashley's story begins with a desire to become a math teacher which in later years included Computer Science classes. A girl with a talent for math taking computer classes? This is her story: What drew you to Data Science from your original education focus? I’d wanted to be a middle or high school math teacher since I was 12 years old. In college, I discovered part of the math major required students to take one computer science course. I took the computer course my first semester of college, and really liked it. Programming was fun! So, to my Math major, I added a Computer Science minor in which I was the only woman. I recall a course in Operations Research in which we’d used mathematics to answer problems in healthcare by using linear algebra to optimize a design for a staffing schedule. This staffing schedule would be used by surgeons for operating rooms. Who knew there was a field where you could solve healthcare problems with math and Data? Once I knew, I dug in. Enter Binghamton University’s Systems Science and Industrial Engineering Department. Though at the time, Master’s Degrees in Data Science didn’t exist yet. But this program at Binghamton had a concentration for healthcare systems. This concentration had it all – courses for Data Science skills like Statistics, Machine Learning, and Artificial Intelligence.  After some of my own horrifying interactions with the healthcare system in the US, and realizing I could use my skills in Math and Computer Science to improve it, then that’s what I wanted to do.  With a graduate research assistantship from The Watson Institute for Systems Excellence (WISE) at Binghamton University, I found myself in the process engineering department at a large care management organization in New York City. It was there I got some real-world experience using clinical Data collected by the hospital to improve processes and solve problems the company had been facing. I was hooked and so I pivoted from Math Teacher to Data Scientist.  It's been 10 years since you started on this path, it seems, what changes have you seen in women in the field and/or STEM focus of young women still in school?  While R and Python are taught a lot more in required courses, there was no such thing as a Data Science Masters Degree when I was in school. Most of the Data Scientists I know have Mathematics, Computer Science, or Engineering degrees. Though we did some light coding in my grad school courses, most of my real programming skills have come from my graduate research assistantship and various jobs I’ve had. Talk about on the job training! When it comes to women in the field, that has grown significantly thanks to hackathons, events, and groups tailored to encourage women to enter the field.  What Do You Think Now?  In 2018, I heard about a non-profit hackathon in Boston called TechTogether whose mission was to end the gender gap in technology, which I thought was amazing. I’m also now part of a few professional groups for women in STEM that meetup in person and have conferences (pre-COVID) or at least have Slack channels.  These advances for women in technology have been great, but there is still a lot of work to be done. I actually attended a talk yesterday by Melinda Gates (who was herself a computer science major) about how the pandemic is affecting women and girls, who mentioned that in the late 80’s when she was in school, women made up about 35% of computer science majors, whereas now in 2020 it’s down to 20%.  Wait, it's Declined? Why is it Do You Think? I was curious about this too. So, I did some digging to try and find data on this, and came across this NPR article which suggests that the share of women in computer science started falling at roughly the same moment when personal computers started showing up in US homes in significant numbers. It was at this time, computers in homes were mostly for gaming, and "computers are for boys" became a popular narrative. A 1990 study shows that families became more likely to buy computers for boys than for girls, even when their girls were really interested in computers. As those kids got to college, computer science professors were increasingly men, and increasingly assumed that their students had grown up playing with computers at home. Surprisingly, this extended even to the 2010s, because I only had one female professor in my computer science department; the rest were male. Not that they were bad professors by any means, but it seemed to me even then that it was much more difficult for women to break into the profession and actually succeed. Needless to say, I was shocked (and thrilled!) when I first read the book Hidden Figures, and found out about NASA's women computers who were essential to putting human beings on the moon.  I think more stories like this have come out since I was in school...I also remember hearing that Edie Windsor, who was already a hero of mine for her LGBTQ rights activism, was a technology manager at IBM. As these stories have continued to come out, I think more women have been able to see themselves as able to do these kinds of jobs, and that is part of the reason we are on the rebound. Though 2020 has been an unusual year by all accounts, it is also the beginning of a decade. What do you see for the future of women in data science and what has your experience been? With the prominence of social media now, I think it’s becoming much easier to find women in your field to connect with and ask for advice and support, and I think this is true for both young girls potentially interested in data career paths and professionals already in the industry.   What steps would you recommend to young professionals entering the data professional path or those looking to change careers? Any job or networking trade secrets you wish you'd known before finding your current position?  Being part of a community and making connections with other women in the field has been very helpful both personally and professionally. Join a club: Girls Who CodeGirlstartSociety of Women EngineersCheck out conferences like Grace Hopper and Women Impact Tech. Just knowing that there are women out there with jobs that you’ve never heard of can be really beneficial to believing that you can do it yourself. Look at people with the job titles you’re interested in, and see what they’ve done in the past as far as jobs, education, etc. Network and establish relationships with other women in your field. This is a very valuable tool both for getting a job and for general professional support. Take every opportunity to network that you can; I’ve gotten most of my jobs through networking and knowing people.  As a Senior Data Scientist and a woman what challenges do women still face in the industry and what's something surprising you've encountered that helped you grow either personally or professionally? I think women still face a lot of challenges in the industry. Firstly, there are just so few of us. In most of my jobs (except for my current one), Data Science teams are largely made up of men.  Document your accomplishments throughout your job and bring it with you when it’s time to talk promotions and raises. It is absolutely crucial to be able to speak up for yourself and be your own biggest cheerleader. I used to think that the way to advance through a career was just doing excellent work and waiting for someone to notice you and give you a raise or a promotion. I’ve found that isn’t true at all, and if you aren’t talking about your own accomplishments, who else is going to? In that same vein, finding mentors, coaches, and sponsors is critical. Finding someone who has seen your work and can speak about it and you to other people is incredibly important.  Your Best Advice? My best advice is to apply for the job, even if you don’t think you’re 100% qualified. If you’re looking for a role in Data Science, Harnham may have a job for you. Check out our current opportunities or get in touch with one of our expert consultants to learn more.   For our West Coast Team, contact us at (415) 614 - 4999 or send an email to sanfraninfo@harnham.com.   For our Mid-West and East Coast teams contact us at (212) 796-6070 or send an email to newyorkinfo@harnham.com.  

The Science Behind the Sales: Statistical Modelling and Consumer Insights

Black Friday, once reserved for the Friday after Thanksgiving, has a new lease on life. It’s not just one day a year. Now, it can be any day of the year. Why? Customers the world over appreciate the deals and discounts as they get ready for the holidays, and the insights gleaned from previous years help businesses determine what will sell best in the current year.  Add in the rise of mobile marketing in which you can buy anything, anywhere, anytime, and more people working from home than ever before, and you have the recipe for Black Friday every day. Especially once the leaves begin to Fall and the holiday season comes knocking at our doors. Behind Advanced Analytics & Insights within the Data profession, there are a host of professions which together help to create the products and launch them. Who could imagine the science behind the sales? Five Important Roles Behind Advanced Analytics & Insights There’s a reason that Data professionals are no longer siloed and must work across and within departments. Data influences every decision within business today. So, having the right people on your team in the right roles can ensure your business thrives. Marketing Analyst Using a spoke-and-wheel analogy, the Marketing Analyst is the spoke. These are the professionals central to taking the information from their Campaign Analysts, Pricing Analysts, and Statistical Modelling experts to determine what will sell best and what price. In essence, their research and Data helps companies figure out ‘what the market will bear.’ Campaign Analyst Focused campaigns to a target market will find a Campaign Analyst understands consumer behaviors. Once the customer is understood – what they buy, when they buy, why and how they buy – can help analysts measure, review, and justify each campaign to justify ROI.Consumer Insights While the Campaign Analyst is focused on targeted campaigns to specific customers, the Consumer Insights Analyst helps businesses tailor their marketing strategies to meet the needs of those customers. All of them. Whether they’re part of a targeted marketing campaign or if they’re prospective clients ‘window shopping’ when they download a ‘free product or click on an email’. Understanding these consumers helps to convert from passing interest to the purchase of a product or service. Statistical Modelling Analyst Do you love puzzles? A jumble of pieces which need to be put together so everyone can see the full picture?  Statistical Modelling are the jigsaw puzzle solvers of the Marketing department. These professionals pull together data from multiple sources and analyze the information to help form a clear picture of their ideal consumer. Toss in a bit of psychology – why customers do what they do and predict what they might do next – and your executives will understand the best way to distribute funds to grow their business. Pricing Analyst It seems simple enough. Determine how much it cost to produce a product or service and mark it up to make a profit, right? Not exactly. These days, calculating not only what it cost to make a product, any overhead to consider, and how much you need to mark it to make a profit is a complex prospect. Factor in what your competition is doing…on a global scale. Consider the fickle buying power of consumers – some days money flows and some days it’s reigned in tight. How do you determine the best price at the right time to ensure maximum profit while keeping pulse on spending patterns? Pricing Analysts take complex data, study customer spending habits, and conduct analyses on what the math says and what the impact might be. So, back to Black Friday sales. Taking what we know of the roles which help businesses set the tone for their marketing strategies, Black Friday every day makes sense. We’re home more. The lines between work and family life are blurred, but computers and phones are at our fingertips, and everyone delivers what we need right to our door. Why not get a jump on your holiday shopping? And once that’s done, you can focus on what your plans are for the future. Are you looking for a career change or just want to see what the market looks like within the Data professionals industry? There is plenty of information to be collected and analyzed. What role might you fill? If you’re looking for a role in Data & Analytics or are interested in Advanced Analytics & Insights, Harnham may have a role for you. Check out our current vacancies or contact one of our expert consultants to learn more.   For our West Coast Team, contact us at (415) 614 - 4999 or send an email to sanfraninfo@harnham.com.   For our Mid-West and East Coast teams contact us at (212) 796-6070 or send an email to newyorkinfo@harnham.com.  

Jumpstart Your Job Search Now and in the Years Ahead

COVID-19 may have rocked the world of employment, but it also created a whole new series of opportunities. If you are looking for work, there are a few updates to the rules of the job search. Not rules, really. More preferred guidelines. A Note on the Guidelines of the Job Search Remember when your work experience was honed to two pieces of paper – your resume and cover letter – and you hoped it made it to the hiring manager? Well, there are a lot more direct ways to get there and plenty of opportunities abound to help you stand out from the crowd. It’s not just your educational experience. In fact, today’s hiring is much more about emotional intelligence, collaboration, and how you use what you’ve learned in previous roles. Among the negative notes, there are a host of positive movements for jobseekers with both established and startup firms. And sometimes, even within a legacy firm which has pivoted with the changes of our new world of work. Thread the Needle of Responsibility Google and IBM may be leading the charge to hire without use of a degree, but most businesses still want that piece of paper. How you present it is another matter. Think video, project portfolios, and online forms via application tracking systems (ATS). That’s just to get you in the door. The more important hurdle is understanding the nuances of your role and responsibilities. The list of qualifications and duties has always been part of the job search. Do you fit all the requirements? Can you handle all the responsibilities? Did you read between the lines to understand what the company hopes will find in their ideal candidate to help them meet their business goals and objectives?  Below are some questions you might ask yourself when reading through job descriptions or considering where you’d like to apply: Are you able to not only craft reports, but also see patterns to help you gain insight into what the reports are telling you?From this, can you not only discuss it with your colleagues and teammates, but also across departments, executives, and stakeholders?Can you not only explain the patterns to both technical and non-technical audiences, but do so across multiple projects?What challenges will you face and how will you solve them?How well do you manage your time? Can you step in to lead a team or do you prefer to work on your own? Could you be flexible between the two?Are you able to build relationships both internally and externally – teammates, vendors, executive leaders, department heads, and the board room.Do you have emotional intelligence? Can you take ownership of a project and hold yourself and others accountable?Do you show initiative? Not just in diving into a project, but asking questions. Can you ask objective questions playing devil’s advocate on one side and seeing the possibilities on the other? These are wide open questions to challenge yourself. Some are leadership-centric. Some are simply ‘can I do the job?’ questions. But, ultimately, it’s these kinds of questions which are asked in interview under the purview of seemingly inane questions. They’re meant to make you think and for the hiring manager to see how you think. 3 Surprising Ways to Stand Out in Your Job Search With the rise of remote working, Zoom, and Slack, the video interview and application process has gained ground. It’s quickly become the virtual way to seek, apply for, meet with, hire, and work with prospective and current team members. But, if you’re in the tech space, you can go even deeper than video and you’ve got more than project portfolios to fall back on. Write about your experiences – what you’ve learned, where, why, and how. Think Medium’s Toward Data Science. Don’t forget to hit publish! Not a writer? Follow the blog and make comments.Network – this seems like a ‘no brainer’, but in our somewhat virtual world it can be even easier for those who already comfortable in this environment. Whether it’s via LinkedIn or Twitch, you are building relationships to help you move forward in your job search.Use your skills to help you run and track your job search more efficiently.  If you’re interested in Big Data, Web Analytics, Marketing & Insight, Life Science Analytics, and more, check out our current vacancies or contact one of our expert consultants to learn more.   For our West Coast Team, contact us at (415) 614 - 4999 or send an email to sanfraninfo@harnham.com.   For our Mid-West and East Coast teams contact us at (212) 796-6070 or send an email to newyorkinfo@harnham.com.  

The Surprising Collaboration of Ada Lovelace, Charles Babbage, and Alan Turing

What do you get when you combine Amelia Earhart with Ada Lovelace? A Data Visualization Engineer ready to work with an aviation industry partner. Reaching new heights and shattering the glass ceiling is the modus operandi for many women, and what better role models than the ladies listed. Creative, free-spirited, pioneering, and well before their time in thoughts and action. Ada Lovelace, now attributed as the first computer programmer saw beyond the automatons of her day. She saw beyond the Berullean language in front of her she was translating.  A poet father and a passion for numbers collided into her thoughts and as we marvel at AI making art, writing stories and music, and winning strategy games, we have one lady to thank. Ada. She might also be called the first Data Visualization Engineer. Don’t you think? Insightful Business Decisions are Key in Collaboration Data professionals are no longer siloed from other departments in business allowing for collaboration between teams. In partnership between both technical and non-technical employees, businesses can be sure they’re teams have a single vision to help realize business objectives and goals. The collaboration between Ada Lovelace and Charles Babbage may not have been business-related, but the ideas are the same. He passed her the document and asked her to translate, she made notes, and those notes have made history. Together they created a vision for The Analytical Machine – it exists only on paper, but it’s design, layout, and potential implementation are realized in ways unimaginable to most 100 years ago.Ada’s mathematical prowess was such that she wrote her notes in easily explainable language.She worked closely with Charles Babbage and wrote in earnest to work with Michael Farraday – she reached out to others in her field, some accepted, others didn’t. How Data Helps Inform the Future Whether you use predictive modeling, machine learning, natural language processing, or some combination of each, the data you collect helps to inform the future. We may often lament the old adage that those who don’t know their history are doomed to repeat it, but history has a shining light as well. Collaboration across the ages. Consider this. Alan Turing, the man who worked in Bletchley Park with the Enigma machine, used the notes he found to help him solve the problem. Those notes belonged to Ada Lovelace. The information she set to paper informed every stage of computer programming leading to what we know today as Artificial Intelligence. Machines that could learn and ‘think,’ not just the automatons of her age which had been ‘programmed to perform.’ The Enchantress of Numbers Known as the Enchantress of Numbers, the pioneering Ada Lovelace shares the spotlight with other pioneering women in the sciences. Think Madame Curie, Joan Clarke, even Hedy Lamarr, and of course Amelia Earhart. They weren’t of the same eras, but each of their contributions have added to what we know as the Science, Technology, Engineering, and Mathematics (STEM). We have a name for it now, but it’s always been around. And the collaborative efforts of women everywhere are growing and increasing diversity and inclusion in many businesses across the world. And at the heart of it all, in the beginning, a surprising and time-defying collaboration began. It set in motion a spark of business intelligence and insight as men and women mentored and partnered for the sake of their vision of the future. Who will be remembered one hundred years from now?  If you’re interested in Big Data, Web Analytics, Marketing & Insight, Life Science Analytics, and more, check out our current vacancies or contact one of our recruitment consultants to learn more.   For our West Coast Team, contact us at (415) 614 - 4999 or send an email to sanfraninfo@harnham.com.   For our Mid-West and East Coast teams contact us at (212) 796-6070 or send an email to newyorkinfo@harnham.com.  

Computer Vision in Healthcare Beyond Covid-19

2020. It sounds like the name of a futuristic science-fiction movie or TV show, doesn’t it? Maybe it is. And like our favorite sci-fi flicks there are cutting edge changes happening in real time. We’re the characters in this story and the Computer Vision and Artificial Intelligence partnerships in healthcare are moving fast to help us take care of ourselves. When computers can see what we can’t. When AI can help us make more informed decisions. When the two are combined to help doctors and providers work more efficiently to save lives, that’s when the cutting-edge shines. From the collaboration of Johns Hopkins, the CDC, and the WHO mapping out the data to contact traces to medical professionals on the front lines, we’ve been focused on one thing. Saving lives. But, what about the other medical issues that affect us? Heart disease. Cancer. Neurological illnesses.  What if the latest advances in healthcare could help here, too? Five Ways Computer Vision Helps Healthcare Providers Identifies leading causes of medical illnesses in a time-sensitive manner by creating algorithms for image processing, classification, segmentation, and object detection.Develops deep learning models to create neural networks.Collaboration of teams of scientists working together for the advancement of projects and present findings to business leaders, stakeholders, and clients.Allows providers to spend more time with their patients.Optimization of medical diagnoses using deep learning so doctors can spend more time with patients to help see and solve the problem faster. Computer Vision Engineer Meets AI Professional Artificial Intelligence (AI) offers real world answers in healthcare the world needs today. Computer Vision Engineers build the means to which AI helps providers, patients, and leaders make informed decisions. Core requirements for both roles include, but aren’t limited to: Experience in machine learning and deep learning.How to build computer vision algorithms and probability models.Problem-solving skills, creativity, ingenuity, and innovation.Languages like Python, R, Hadoop, Java, and Spark.Be able to see the big picture while at the same time finding the devil in the details. Always striving to improve, to make better, to advance the technology within the industry. The Challenges and the Potential of Technology in Healthcare At the moment, Computer Vision, AI, and other healthcare technology models are localized to individual placements. The next step is to have these technologies ‘speak’ to each other across hospitals, provider’s offices, telehealth applications, and electronic health records management for a more cohesive benefit of care. As this year rounds to a close, we know the vulnerabilities of our healthcare system, and can find solace in the though that technology is bringing it forward at lightning speed. Automation and telehealth appointments have made it a breeze to talk to our doctors and get results faster. We can pay our bills with the click of a button and even carve out a payment plan, if need be. All without leaving our homes. The data now available to us and our providers offers a foundation, a benchmark of information, so our doctors can make more informed decisions. This data goes beyond the individual, it helps set a precedent for not only individuals, but also entire populations, to help us identify future health issues, epidemics, and pandemics.  Stored data is private and stays within its construct of hospital or doctor’s office, but from it we can create models to plan for the future. Want to make your make your mark in the healthcare and tech industry? We may have just the role for you. Check out our current vacancies or get in touch with one of our expert consultants to learn more.   For our West Coast Team, contact us at (415) 614 - 4999 or send an email to sanfraninfo@harnham.com.   For our Mid-West and East Coast teams contact us at (212) 796-6070 or send an email to newyorkinfo@harnham.com.  

A Slam-Dunk Career as a SLAM Engineer

Philadelphia. It’s known for it’s Philly Cheesesteak, the Liberty Bell, and where the Constitution was signed. Always on the cutting edge, Philadelphia is a land of firsts. You may or not know this, but one of its firsts was to have the first general use computer in 1946. Is it any wonder then that a company there is building robots to navigate GPS denied environments and was begun by leaders in the Computer Vision space?  Beyond the Roomba If you consider the Roomba, the autonomous vacuum that sweeps up pet hair, dirt, and other unwanted product, how does it know where to go? How does it know to go under a table or chair or around a wall to the next room? How does it know to avoid the dog, cat, or you? On nearly the smallest scale, this little round machine is a personal version of simultaneous location and mapping (SLAM).  However, the computational geometry method of this mapping and localization technique extends in a wide variety of arcs. Here are a few to get you thinking: GPS Navigation SystemsSelf-driving carsUnmanned Aerial Vehicles (UAV)Autonomous Underwater Vehicles (AUV)DronesRobotsVirtual Reality (VR)Augmented Reality (AR)Monocular Camera...and more There’s even a version which is used in the Life Sciences called RatSLAM. But we’ll visit that in another article. The uses and benefits of this simultaneous location and mapping technique are exponential even with some of the challenges posed by Audio-Visual and Acoustic SLAM. What is SLAM? Essentially, it is the 21st century version of cartography or mapping. Except in this case, not only can it map the environment, but it can also locate your place in it. When you want to know where the nearest restaurant is, you simply type in ‘restaurant near me.’ And soon, a list appears on your phone with a list radiating from nearest location outward.  Imagine you’re lost on a hike, you manage to find signal, and soon your GPS is offering directions on which way to move toward civilization.  This is Simultaneous Localization and Mapping. It locates you, your vehicle, a robot, drone, unmanned aerial vehicle or self-driving car and puts people and things in the direction it thinks they want to go or should go to get to safety. While mapping is at the epicenter of SLAM Computer Vision Engineering, there are other elements within the field as well. But let’s begin with mapping. Topological maps offer a more precise representation of your environment and can therefore help ensure consistency on a global scale.  Just as humans do when giving directions, sensor models offer landmark-based approaches to make it easier to determine your location within the map’s structure and raw-data approaches which makes no assumptions. Landmarks such as wifi or radio beacons are some of the easiest to locate, but may not always be correct which is where the raw-data approach comes in to offer its two cents as a model of location function. Four Challenges of SLAM GPS sensors may not function properly in chaotic environments such as military conflict. }Non-static environments such as pedestrians or high traffic areas with multiple vehicles make locations difficult to pinpoint.In Acoustic SLAM, challenges include inactivity and environmental noise as well as echo. Sound localization requires a robot or machine to be equipped with a microphone in order to go in the requested direction. Five Additional Forms of SLAM Tactile (sensing by touch)RadarAcousticAudio-Visual (a function of Human-Robot interaction)Wifi (sensing strength of nearby access points) Ready to Explore a Robotics and Computer Vision Career? Whether you’re interested in a slam dunk career as a SLAM Engineer or looking for your first or next role in Big Data, Web Analytics, Advanced Analytics & Insight, Life Science Analytics, or Data Science, take a look at our current vacancies or get in touch one of our expert consultants to learn more.   For our West Coast Team, contact us at (415) 614 - 4999 or send an email to sanfraninfo@harnham.com.   For our Mid-West and East Coast teams contact us at (212) 796-6070 or send an email to newyorkinfo@harnham.com.

How Machine Learning and AI Can Help Us See the Forest for the Trees

In the early days of 2020, Johns Hopkins, the CDC, the WHO, and a host of other public organizations banded together in collaboration. They were on a mission to ensure the world had real-time information to a virus that would forever chance the course of this year and the years to come. Which is great for those families with a computer in every home or every person with smartphone access. But what about the rest of the world? How do you ensure those people without access to basic needs lives can be improved? A health non-profit using AI and Machine Learning is aiming to do just this. But the Data is vast and the sheer numbers of people need to be corralled by someone into something the computers can read and make decisions on. Who would have thought Public Research and Data Science would come together in such a manner and in such an important time? Three Benefits of Data Science and Machine Learning in Healthcare According to a seminar given in September 2019, two research scientists explained to the CDC the promises and challenges using Big Data for public health initiatives. After explaining a few definitions and making correlations, the focus was soon on the benefits. The focus of Machine Learning is to learn data patterns.From the initial focus, patterns can then be validated to ensure they make sense.These patterns and validation of patterns can find links between seemingly uncorrelated factors such as the relationship between one’s environment and their genetics. To the scientists working with these scenarios, the decisions seem simple. Yet, when it comes to explaining them to laymen like policymakers, there can be a shift in understanding. This shift can lead to arbitrary and different findings which can affect medical decision making. Why? Could it be using Random Forests in linking the data could be confusing?  Data Classification is Not as Cut-and-Dried as a Work Flow or Org Chart If someone shows us a work flow or organizational chart, we understand immediately each task to be done in which order or who reports to whom. But in trying to link uncorrelated bits of information using decision trees, it can seem more like abstract art, more subjective than direct. Yet, it is those correlations which answer the bigger questions brought to bear by Research Scientists, Public Health Researchers, the Data Scientists, and AI working together to see the bigger picture. Decision trees, ultimately, are the great classifier. But there are a few things which need to be in place first. Yet, in the random forest model it’s not just one decision tree, it’s many. This is definitely a case where, if you done right, you will see the forest for the trees and at the same time be able to determine patterns in those trees. A bit counter-intuitive, but this is what stretches our minds to see correlations and patterns we might not see otherwise, don’t you think? So, what do you need to help make predictions?  Two Important Needs to Help Make Predictions Predictive power. The features you employ should make some sense. For example, without a basic knowledge of cooking, you can’t just throw random items from your refrigerator into a pot and expect it taste good. Unless of course, you’re making soup and all you have to do is add water.The trees and their predictions should be uncorrelated. If you’ve ever seen M. Night Shymalan’s Lady in the Water, there’s a little boy who can ‘read’ cereal boxes and tell a coherent story. A predictive coherent story. This is the layman’s version of random forests, their predictive nature, and ultimately, the scientists who can ‘read’ and explain the patterns. If you're looking for your first or next role in Big Data, Web Analytics, Marketing & Insight, Life Science Analytics, and more, check out our current vacancies or contact one of our recruitment consultants to learn more.   For our West Coast Team, contact us at (415) 614 - 4999 or send an email to sanfraninfo@harnham.com.   For our Mid-West and East Coast teams contact us at (212) 796-6070 or send an email to newyorkinfo@harnham.com.  

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