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Bridging the Gap: The Role of a DevOps Engineer

Siloed teams are swiftly becoming a thing of the past as organizations learn collaboration is key. Businesses are embracing transformation. But some may not know where to turn to help them manage such a massive restructuring of operations. Enter the DevOps Engineer. Yes, Virginia. The unicorn employee does exist. What is a DevOps Engineer? For many businesses, it’s a dream to find a technical person who can also communicate across departments. In the DevOps Engineer role is an IT Generalist who not only has a deep understanding of codes, infrastructure management, and agile familiarity but who also possesses interpersonal skills. It’s this combination that makes this role so imperative to businesses. Working across siloes and bringing teams together for collaboration bridges the gap between the technical and non-technical departments. One of their most important roles is as advocate. Moving from siloed teams to the more collaborative environment of a DevOps culture can be difficult for engineering team members. But as advocate for the benefits, the DevOps Engineer can explain it best to those with whom they’ve worked. Their technical expertise puts them on par with their peers and their interpersonal skills offer a way to communicate across the organization.   Want to Restructure Your Skills toward DevOps? If you’re an IT Generalist with great communication skills. DevOps Engineer could be your next role. But what skills do you need and how might you streamline what you already know into this key role for many businesses? Technical skills depend on team structure, technologies in place, and tools already in use. But the key element of a DevOps Engineer is their strong communication and collaborative skills. Can you morph your technical world into layman’s terms for the executives? Can you translate different needs across teams from QA testers to software developers, generalists and specialists alike? It’s this deep understanding which makes you so valuable to employers. For many organizations, this is the best of both worlds.  Knowing the pros and cons of available tools. Understanding the components of a delivery pipeline. And strong communication skills to bridge once siloed teams into a cohesive and collaborative environment. More technical skills include, but aren’t limited to System administration – such as managing servers, database deployment, and system patching just to name a few.Experience with DevOps tools – understand the lifecycle from building and infrastructure to operating and monitoring a product or service.Configuration management – experience with configuration management tools such as Chef, Puppet, or Ansible to automate admin tasks.Continuous Integration (CI) and Continuous Deployment (CD) – this is a core practice of DevOps. It’s this role’s approach to software development with tools to automate the building, testing, and deploying of software processes. System architecture and provisioning – ability to design and manage computer ecosystems whether in-office or in the cloud. Within this skillset is the importance of Infrastructure as Code (IaC). This is an IT management process that applies best practices from software development to cloud infrastructure management.  Collaborative management skills – while the CI/CD skills are core to the technical side, this is one of the key components for the soft skills required for a DevOps structure. In a Nutshell DevOps (Development + Operations) is a practice that involves new management principles and requires a cultural change. And a DevOps Engineer is the heart of the transformation. Yet they can’t do it alone. A good DevOps Team has more than just one engineer. It involves a mix of generalists and specialists to implement and improve these practices within the software development cycle. A few of these roles include:  DevOps evangelist Automation expert Software developer Quality assurance  If you’re interested in Big Data and 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.  

Amped Up Analytics: Google Analytics 4

Google Analytics 4 has amped up data insights into the behaviors and preferences of your customers. Where once each touchpoint only tracked what had been clicked, GA4 is bringing it all together in a more wholistic approach to the customer journey. As the fourth quarter of 2020 dawned, Google upped its game. Crafting a compelling array of features with machine learning at its core, this new platform offers a more customer-centric approach to data-driven insights, rather than split data across platforms and devices.   Though still in its infancy, there are some dramatic new changes afoot. And while it’s not a good idea to get rid of the old Universal Analytics platform before ringing in the new one, it is a good idea to understand what’s available now and what may come to be over time. Four Advantages to Google Analytics 4.0 From our desktop to our laptop to our smartphone, we carry our office in our pocket or on our lap. So, what better way to integrate what was once called “App + Web properties” into a more cohesive trackable measurement of data. Add to this the privacy protocols in place to protect customers, and Google Analytics 4 offers flexibility for future cookieless tracking and permissions, and advantages are revealed. Combined Data and Reporting Rather than focusing on one property (web or app) at a time, this platform allows marketers to track a customer’s journey more holistically.  The platform’s premise is that there is a pattern everyone follows. From the moment a customer visits your website to clicks on a button subscribing to your newsletter or blog – Acquisition and Engagement. To the moment your customer makes a purchase, is happy with the product or sevice, and comes back again – Monetization and Retention.  Designed for marketers who want to track users across multiple formats, Google Analytics 4 hopes to solve with Data Streams. These Data Streams merge to paint a picture of the customer journey from website visit to purchase. A Focus on Anonymized Data This anonymization answers the call to Data Privacy and third-party data collection. Crafting a unified user journey centered around machine learning to fill in any gaps, marketers and businesses have a way to get the information they need without diving into personal data issues. This is a key change in that Google is moving away from client-side focus and using server-side and customer-centric capabilities. With GDPR and privacy laws in full swing, marketers face enhanced privacy regulations as cookies are phased out or blocked. Predictive Metrics and Audiences Using Machine Learning to predict future transactions is a game changer for the platform. These predictive metrics for e-commerce sites on Google properties allow for targeted ads to visitors who seem most likely to make a purchase within one week of visiting the site.  Though focused on e-commerce sites now and based on transactions and revenue, there is an opportunity for marketers to identify and convert based on such leads as video views or form submissions. Machine Learning-Driven Insights The launch announcement for GA4 explains it “has machine learning at its core to automatically surface helpful insights and gives you a complete understanding of your customers across devices and platforms.” Machine Learning-driven insights include details that elude human analysts.  What These Changes Mean on the Digital Frontier We’re all reaching for higher value and Google Analytics 4.0 brings it into one unified platform for the future. As we make the shift from traditional Google Analytics to its 4.0 version, there is opportunity to get more creative.   Wondering if you should upgrade? This article breaks down the pros and cons to help you decide.  If you’re interested in Big 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.  

Making Sense of Unstructured Data with NLP

Natural Language Processing. It seems a simple enough explanation. The idea is to make computers sound like native speaking humans regardless of their language. Except there’s one problem. When we speak, we don’t follow our own rules of grammar. We use idioms, metaphors, abbreviations, and oftentimes use more body language to communicate than we realize.  So, what’s a poor machine to do when confronted with such an unstructured melee of data? Well, since semantics is not what you say it’s how you say it, we must teach computers to read between the lines. Of code. Enter NLP. The semantics of human language written for a machine to help make sense of our human behaviors gets organized. The Perfect Imperfections of Language Computers require structure. Natural language does not. Teaching machines how we communicate is no easy task, and yet we use machines that can do this every day. By combining technology and Machine Learning we begin to teach computers how to understand us. We teach them how to interpret and determine what it was we want done. When you’re asking Siri or Alexa a question, you’re helping them to learn how you ask, so they can better respond, and they make you more efficient. It’s a win-win for everyone. In business, using NLP techniques to drive business decisions is even more important. Now, the computer must decide what information is the most valuable to pull from a pile of Data. Understanding our choices, our tone, even the words we choose to use, helps our machines learn what we want to do or need done. Where is NLP Used? Since we use different rules when we speak than when we write, our computers learn how we talk and how to use language more naturally. Wondering where NLP might be used? In a word or two? Nearly everywhere. You are scheduling a meeting and when it’s time, a calendar reminder pops into your phone which says estimated drive time to the meeting based on traffic conditions in your area. Or you ask Alexa to play your favorite music list from Pandora.  Every touchpoint in this scenario is using NLP. We naturally might get into our car, ask our Virtual Assistant navigation system for directions, or to play our favorite music. Our choices don’t fit in a box and may not be logical, but the more we teach the machines, the closer they may get to understanding the nuances of our language. Here are 5 more ways we use NLP every day: Predictive text on your phone or in your Word document. Chatbots and Virtual Assistants to ensure customers are acknowledged in a timely manner, answer basic questions or redirect to appropriate personnel, and making suggestions to improve the customer experience.Curating social media feeds to determine customer needs and interest.Grammar correction software so our emails and business documents are error-free.Analyzing customer interactions using comments and reviews for customer feedback about a product or service. There’s a ton of information to be filtered, sorted, sifted, and analyzed, and NLP is just one of the tools Data Scientists use. Interested in the subfield of NLP? Check out this article for 6 techniques you need to know to get started. Already well-versed in the industry and looking for a new challenge? If you’re interested in Big Data and Analytics, Advanced Analytics, Life Sciences, Data Science, or any of our Data professional fields, we may have a role for you. Review 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.  

Smile: How Tech is Transforming the Dental Industry In 3D

Ever wondered what’s new at the dentist’s office? If you’re in the hot seat for dentures, crowns, or braces, you may be surprised at the speed you find yourself with a new smile.  Imagine a new set of teeth printed layer by layer before your eyes. Ok, before your dentist’s eyes. 3D printing has been used to print prosthetic limbs, orthopedic and cranial implants, surgical instruments, crowns, and dental restorations.  Electronic Health Records. AI-assisted surgeries. Machine Learning algorithms for more efficient workflows in hospitals and doctors’ offices. Medical technology isn’t new. But what about dental technology? In the Life Sciences field, technology is helping to shape the future of how we heal.  What is 3D Printing? According to the FDA, “3D printing is a process that creates a three-dimensional object by building successive layers of raw material. Each new layer is attached to the previous one until the object is complete. Objects are produced from a 3D file, such as computer-aided design (CAD) drawing or a Magnetic Resonance Image (MRI). The flexibility of this technology allows creation of individualized products such as prosthetics, dentures, or crowns specific to the individual requiring the device.  “It’s Not the Drill, It’s the Bill” Borrowed from an old commercial, the tagline originally implied patients weren’t afraid of the dentist, but of the bill at the end of the appointment. But with today’s technologies, particularly through the benefits of 3D printing, this tagline isn’t quite so dramatic. Here are a few ways, 3D printing in dentistry is benefitting both doctor and patient.  1. The Lab is Onsite Cost savings begin here. When the dentist can do his or her own lab work onsite, it’s less cost to consumers and to the dentist office’s bottom line. Add in the user-friendliness of the available 3D machines which allows dentists to produce molds, models, crowns, bridges, there’s plenty of opportunity to be more efficient and have more control over time and quality of the product.  3D Printers range in price from $20,000-$100,000+ for industrial printers. If you have a dental practice, you could most likely snag a desktop model for around $6,000 or less. Compare that to over $100,000 for outsourcing lab work, labor, and shipping costs included. 2. Getting it Right – More Accurate and Faster Services Reduce errors and increase accuracy when using 3D printing to convert digital images into physical objects within minutes. Watch as your patient’s dentures, for example, are printed layer-by-layer and usable with minutes, not hours or days.  Your technician can get to work as soon as the scan is ready and won’t be inhaling plaster or grinding dust while they work. A clean work space is a safe work space, no matter the industry. 3. Better Quality Products  Skilled dental technicians are still in high demand. But with the advent of 3D printing, their jobs are made a bit easier, and they’re able to design and create better quality products. Milled models could wear down over time. But a 3D model offers more stability and durability than its predecessor. Additionally, this digital model creates a more complex structure and offers a higher level of detail that may not be available in more traditional modeling techniques. 4. Enhanced Patient Experience 3D printing technologies have enhanced patient experience by reducing anxiety and increasing patient acceptance. How? Well, when you can print a model to help explain what’s going to be happening to identify and solve a patient’s problems, it can help alleviate their stresses of the unknown. Add to this a more efficient workflow, more aesthetically pleasing products, and less invasive treatments which make the patient’s visit go more smoothly, and you have a satisfied customer. 5. Save Money Last, but not least, is probably the biggest benefit to both patient and provider. Saving money. Though the upfront investment in a 3D can run into around $20,000 for a top model, it includes all the necessary components printer, reduces the need for skilled staff to produce dentures, implants, and other dental restorative models.  These savings are then passed on to the patient not only monetary value, but in time. The more accurate, efficiency, and speed of 3D printers means less time at the dentist’s office. Less return visits. Less error. With an estimated savings up to 80 percent depending on patient’s needs Smile. Tech is transforming the dental industry. Want to see where it can take you? If you’re interested in Big Data & Analytics, Advanced Analytics, Life Sciences, Data Science, or any of our Data professional fields, we 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.  

Zoom Fashion: Five Marketing Insights From A Remote World

Remember Fashion Week? That place where Designers shared their imagination on stage, and models wore outfits which seemed out of this world. Remember the mall? That place where you found clothes to make you stand out as an individual in your surroundings. Now that we’ve been quarantined and social distanced for a year, and our office is our living room, fashion doesn’t play so much into our daily lives. Or does it? Sure, it’s had to change just like we have. Actually, it’s because we’ve changed. Where once consumers followed fashion, now fashion follows the consumer. From the Digital Transformation with AI to the call for comfort, the fashion season has changed. Here are a few insights as to how. Five Marketing Insights on the Future of Fashion Demand Is Down  Whether you work from home or at a remote location, the rules of office fashion have changed. So has formal wear fashion for that matter. With no events to attend, no weddings in play, and most restaurants closed, the need for clothes to wear for specific outings have fallen out of favor.  Add in a mix of unemployment and slowed spending – choices focused on food and rent versus clothing, footwear, and accessories, and the fate of fashion seemed completely downgraded. But companies with a conscience, and those focused on leisure and activewear, have an opportunity to bounce back. Consumers working from home are focused on casual for business, and comfort for consumers interested in health and wellbeing. Digital Is Up Online sales, virtual customer service, and digital transformation of the retail industry have bloomed within just a few months. Shopping is social and brands have had to keep up.Since the debut of finding fashion fits in a videogame-like format which allows you to virtually try on different styles of clothing, haircuts, shoes, or design your own accessories, fashion has gained ground in VR. Though brick-and-mortar stores aren’t out of the game yet, online sales will reign. Fashion brands are finding ways to adapt and balance the needs of their consumer from a mix of online, virtual experiences with a human touch. Classic Comfort Whether we’re in bunny slippers, slipper socks, or bare feet as we pad across the living room to our computer, we can feel a little childish glee that slippers are estimated to grove 50% or more this year. Add in our most comfortable set of lounge pants, and all we have to worry about is a top that seems business-y enough for our Zoom meetings, right? Though the pandemic has escalated consumer desires for comfort and casual wear, most were already in the mindset – even before work from home and remote working became the new normal. However, with the consumer mindset focused on form and function versus the latest and greatest, much of the fashion industry has faced major overstock issues. Consumers now want clothing that’s better made, lasts longer, and is more sustainable. These new consumer demands and facing overstock issues have forced brands to improve Insight Analytics for the industry. Social Justice Is On The Line Brands who focus first on their employees and vendors are more likely to win the hearts of today’s consumer. Shopping is still social. But now it comes with a social justice impetus to pay workers fairly for their work as they learn about pay structures or lack thereof for garment workers and sales assistants.  Ultimately, consumers are calling for authenticity and transparency. Brands who engage authentically at every level of their logistics and supply chain, could more easily find common ground and a boon of support from shoppers for showing they care. AI-Focused Fashion Gains Ground AI and Machine Learning are helping brands at scale and offering consumers a unique virtual experience. From chatbots to smart image recognition systems, AI is transforming the industry at every level – manufacturing to quality assurance to design and Marketing and sales. Outside the making of the products, AI is facilitating change and improving the shopping experience. Using Predictive Analytics, Advanced Analytics, and intelligent automation, it is improving the efficiency of the consumer’s journey.  Though fashion has definitively shifted online, that doesn’t mean there’s no room at the table for brick-and-mortar space. Opportunities exist for a blend of digital, pop-ups, and temporary locations so brands can expand their reach at every place consumer’s might prefer to shop. But in the digital space, ecommerce and mobile apps are a focus for consumers and fashion brands alike as it offers a ‘try before you buy’ within a virtual medium. If you’re interested in Big Data & Analytics, Advanced Analytics, Life Sciences, Data Science, or any of our Data professional fields, we 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.  

The Women Who Brought Us Wi-Fi, WFH, and More

It seems almost counterintuitive to lament the statistics of women in tech when you realize how many women, throughout history, helped to build the world of technology. Some names you may know. Ada Lovelace. Hedy Lamarr. Karen Johnson. Grace Hopper.  The list is long and these few names barely scratch the surface. But you have these ladies to thank for computer programming, wi-fi, and human mathematical ‘computers’ which have paved the way for so much of what we can do today. In honor of Women's History Month, we wanted to celebrate both the women of technology who set the stage for us to work from home on computers using wi-fi to the women of tomorrow.  Women in Tech Isn’t New Near the turn of the 20th century, a ‘woman’s work’ went well beyond the kitchen. Yet, it was a housemaid who was tasked with crunching the numbers from raw Data gathered by the men of the Harvard Observatory. When the men declined to analyze their Data deeming it ‘clerical’ and therefore, women’s work, the head of the Observatory needed help. Enter Williamina Fleming, housemaid to Edward Pickering, head of the Harvard College Observatory. Williamina would go on to lead 80 ‘computers’ at Harvard. Enter The Women of ENIAC, the first computer programmers. Though the ENIAC itself was built by men, it was a unit of six women who would actually do the coding on the machine. Their calculations plotted missile trajectories on behalf of the U.S. Military. These women would go on to become mathematicians at NASA and its Jet Propulsion Laboratory. And Grace Hopper, known as the ‘mother of computing,’ helped develop the COBOL language. She also helped develop the UNIVAC I computer, the first business-focused computer. The Old Normal Would you believe the idea of working from home began with a woman bringing home her computer to write its operating systems manual? As you commute across your home from your non-work life to your working life, cup of coffee in hand, thank Mary Allen Wilkes. She’s credited with being the first person ever to have a personal computer in her home.  And there would be no working from home without wi-fi. Hedy Lamarr, the famous actress of the 1940s was also a brilliant scientist. She loved to see how machines worked and helped develop what would become wi-fi. The Pioneering Women of Today in Tech   From AI to Machine Learning to Coding, women are leading the way. Not only are their businesses data-driven, but there is a strong focus on diversity and inclusion both for human and machine. Danah Boyd, founder and president of Data & Society, is keeping an eye the on ethical and legal implications of emerging technologies. Some topics she’s focused on include accountability in machine learning and media manipulation. Want to know what’s next in the world of tech? Meet Cathy Hackl, one of LinkedIn’s Top Tech Voices and the host of the Future Insiders podcast. She focuses on AR and VR working with name brands on the how best to use these technologies.  Dr. Fei-Fei Li, co-director of Stanford's Human-Centered AI Institute is a pioneer of not only AI, but also Computer Vision. Her nonprofit, AI4ALL, is intended to improve diversity within the field. But it’s her ImageNet project which holds the most sway. The images in this database have helped ‘train’ computers how to recognize what they see. Katie Moussouris is an unlikely heroine in the world of security. Cybersecurity. In the world of Data privacy and security, we may not automatically think of a woman. But we might imagine a hacker who would use their powers for good. The founder and CEO of Luta Security, Katie Moussouris, is the best of both worlds and is busy protecting businesses and government agencies from digital threats. With a focus on diversity and inclusion in the fields of Data and Technology, Kimberly Bryant, started Black Girls Code. Her aim is to create a more diverse computer programming course. An electrical engineer herself, she was determined her daughter not feel culturally isolated or give up her passions.  These women are the tip of the iceberg of women in tech today. As a recent interviewee suggested, we encourage you, if you’re interested, to join organizations and networks that support women in data and technology fields. At Harnham, we’re proud to partner with Women in Data. If you’re interested in Big Data and Analytics, Life Sciences, Data Science, or any of our Data professional fields, we 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.  

CRO: Getting Customers Past Your Digital Door

Conversion Rate Optimization. CRO. If you’re an established business just getting on the technology track to improve your business, these words and acronyms can sound difficult and confusing. So, let’s put things a little simpler. Your website is your digital doorway to your business. Your service is your digital handshake. When you’re able to meet with customers face-to-face, you can get a firmer grasp on their likes and dislikes. You get to know your customers over time, they get to know you, and you begin to learn what the want so you can improve your business. If you’re a startup, you’ve opened your business because perhaps you’ve been a customer and saw a need no one could fill but you.  Whichever type of business you are, when you make changes to your website to improve your customer experience, you’ve worked through conversion rate optimization, though you may not have realized at the time. What is Conversion Rate Optimization? It is the penultimate testing strategy to convert visitors into customers. Let’s assume your eCommerce business is bringing in leads, but no one is clicking the ‘buy now’ button. If you’re wondering why, this is your chance to test your CRO through A/B testing. This kind of testing examines your original version against a change in your wording or colors. Consider the number of times you’ve seen Amazon’s logo change over the years. Today, the name is no longer needed, only the smiling arrow. The simplest of tweaks to your call-to-action (CTA), logo, colors, wording, or even a well-read or reviewed article can drive more leads for your business. Simple testing with big consequences can be overwhelming to consider. But with a few key points to consider, you may have a better focus on what you need to do. This focus will help you identify your goals, your audience, and the best conversion touchpoints for your business. What Do You Want to Optimize? Conversion means many things to many people. While ultimately the goal is to convert visitors to customers, there are a variety of ways to get there. So, what do you want to do? Do you want to have more visitors call or fill out your contact form? Do you want new subscribers to your website? Or do you want your visitors to click ‘buy now’ or ‘add to cart’? Choose one goal and work from there. Data you may already have or can gather, can offer you insight into your customers to help you know the best way to move forward. Know Your Customer Digital and Web Analytics can help you navigate the Data gathered about your customers. For example, who’s already visiting your site? How did they find you? Age, gender, and location are additional demographics which may help your team make informed decisions about what to test, why, and how it will improve your conversion rate. Bringing Your CRO Team Together There are three main roles most often brought together for conversion rate optimization. Smart businesses make CRO a part of their Marketing Strategy. So, it’s only fitting Marketing is on the list.  Marketing - These are the professionals who understand people. They know the strategy behind every level of the sales funnel within the customer journey. And from these understandings, they can troubleshoot, if needed, with acquisition, qualification, or optimization. Acquisition – These are the professionals responsible for bringing in new business. New leads. New customers. It’s their experience which can help to identify what’s optimizing well and what isn’t whether from targeting the wrong data point or on-page issues. Web Developer or Designer – These professionals assist with the technical aspects of conversion rate optimization. Begin at Your Homepage If you’re wondering where to begin, it’s best to begin at the homepage. This is where prospective customers find you and determine whether they’d like to look around a little more or not. So, knowing this there are a few things to keep in mind. ABT – Always Be Testing. This is a circular exercise in keeping up with the Jones’s of business. The more you know about your site, your goals, and your customers needs, your improvements can help to generate leads and increase sales. OTE - Optimize the Experience. When setting your goals, you’ll want to consider three goal types and set one or more. The first is to ask yourself, what do you want to happen immediately? If you want more clicks or views, this is an immediate goal. If you have a finite amount of time to generate leads, say fourth quarter of a given year, you may wish to set a campaign goal. And if you want to project net revenue or lead quality, you’ll want to set a long-term goal. Ready to optimize your conversion rate in your job search? Harnham may have a role for you. If you’re interested in the Digital Analytics, Data & Technology, or Machine Learning 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.  

Black History Month: Ethical AI and the Bias Within

According to Brigette Hyacinth’s 2017 book entitled, The Future of Leadership, the author suggests this when considering the ramifications of AI. “Using AI to improve efficiency is one thing, using it to judge people isn’t something I would support. It violates the intention on the applications of AI. This seems to be social prejudice masquerading as science…” How often have big tech companies backtracked their facial recognition software? What are the ethical implications of moving forward and leaving AI unchecked and unregulated? 2020 was in no way a traditional year amassing change on our daily lives at near lightspeed, or so it seemed. But what was brought to bear were unrest and tensions boiled to the breaking point. And when you look at it from the perspective of AI in our daily lives. What might the world look like in another year? When Social Sciences and Humanities Meets AI “To err is human, to forgive, divine.” Humans make mistakes. Biases are unmasked with and without intent. But, when it comes to AI, those unintentional biases can have devastating consequences. From 2015 to 2019, use of AI grew by over 250 percent and is projected to boast a revenue of over $100 billion by 2025. As major businesses such as Amazon and IBM cancel and suspend their facial recognition programs amidst protests against racial inequality, some realize more than regulatory change is needed. Since 2014, algorithms have shown biases against people of color and between genders. In a recent article from Time.com, a researcher showed the inaccuracies of prediction for women of color, in particular. Oprah Winfrey, Michelle Obama, and Serena Williams skewed as male. Three of the most recognizable faces in the world and AI algorithms missed the mark. These are the same algorithm and machine learning principles used to challenge humans at strategy games such as Chess and Go. Where’s the disconnect? According to one author, it may be time to create a new field of study specific to AI. Though created in Computer Science and Computer Engineering labs, the complexities of human are more often discussed in the field of humanities. To expand further as well into business schools, race and gender studies, and political science departments. How Did We Get Here? At first blush, it may not seem comparable to consider human history with the rise of artificial intelligence and its applications. Yet it’s human history and its social construct which explains the racial and gender biases when it comes to ethics in AI. How deep seated are such biases? What drives the inequalities when AI-enabled algorithms pass over people of color and women in job searches, credit scores, or assume status quo in incarceration statistics? Disparities between rational and relational are the cornerstone from which to begin. Once again, in Hyacinth’s book, The Future of Leadership, the author tells a story of her mother explaining the community around the simple task of washing clothes. Though washing machines now exist and do allow people to do other things while the clothes are washed, there is a key element recounted by her mother washing machines lack. The benefit of community. When her mother washed clothes, it was her and her surrounding community. They gathered to wash, to visit, and connect. A job was completed, but the experience lingered on. And in the invention of a single machine, that particular bit of community was lost. But it’s community and collaboration which remind humans of their humanity. And it’s from these psychological and sociological roles, artificial intelligence should learn. Create connections between those build the systems and those who will use them.  BUILDING AI FORWARD Voices once shuttered and subjugated have opened doors to move artificial intelligence forward. It is the quintessence of ‘those who don’t know their history are doomed to repeat it’. The difference within this scientific equivalent is there is no history to repeat when it comes to technology. And so it is from the humanitarian angle AI is considered. The ability to do great things with technology is writ in books and screenplays, and so are its dangers. While it isn’t likely an overabundance of ‘Mr. Smiths’ will fill our world, it is important we continue to break out of the siloes of science versus social sciences. If AI is to help humanity move forward, it’s important to ensure humanity plays a role in teaching our machine learning systems how different we are from each other and to consider the whole person, not just their exoskeleton. If you’re interested in the Data Sciences, Data and Technology, 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.  

Puzzle and Problem-Solvers: Software Engineers Drive Business

Software. It’s the drivers to your printer. It’s the word processor on your PC. And it’s the concept behind your productivity tools, your CRM systems, and your social media programs. Software engineers are to software what Data Engineers are to Data.  Software Engineers are the creators, builders, and maintainers of software systems and programs, so business runs smoothly. Now, that the majority of businesses have shifted online, it’s more important than ever to keep things running smoothly. These engineers must take into account not only what businesses might need to run, but also the limitations of the program. It’s a balancing act of software, hardware, limitations, and possibilities. If you took apart watches as a kid to see how they worked, Software Engineering might be for you. Are you a problem solver? Do you love putting the pieces of a puzzle together whether it’s on a board or in a crossword? Software Engineering might be for you. What Kind of Software Engineer are You? While there are a variety of roles to consider, below are some of the more popular paths taken. So, let’s say you want to build computer applications that affect what the end user sees. If you know programming languages such as Python and Java, and understand the mechanics of how to make a program work, then you may fit the classic example of a Software Engineer. If you’re more interested in the focus of robotics or automation, you may want to consider a role in Embedded Systems. You’ll still be designing, developing, and maintaining but your projects will be hardware and software used for a specific task.   Want to keep information secure? You may lean toward Security Engineer. In this role, you’ll ensure there are no security flaws. How? By operating as a ‘white-hat’ ethical hacker to attempt breaking into existing systems to identify threats. Technical Skills are Essential. Soft Skills are Important.  For anyone in the Data professions, technical skills are paramount. This not only gets your ‘foot in the door’, but ensures you know the basics. And for those who’ve been in the game a bit longer, also gives businesses confidence you can meet any challenges which may come up. Technical skills for Software Engineers include knowing programming languages like C++, Python, Java, and others like them. In this role, you’ll need to understand development processes as well as additional technical concepts. Technical skills are a standard requirement. And as important as it is to have a good portfolio and experience, you’ll want to show the business, you have the technical know-how to take on anything which may come your way. Now that cross-functional teams across departments are regular occurrences and C-suite executives are in the know, soft skills are just as important as technical skills. What are Soft Skills? In a nutshell, soft skills are communication skills. In the past, Data professionals may have been siloed away from other teams, and a liaison of sorts might have translated Data information into actionable insights. Now businesses and professionals have found it’s much more efficient to have the Engineer speak directly to their team, their leadership, or stakeholders. So, it’s imperative your soft skills are on par with your technical skills. Scope of Work for a Software Engineer According to the Bureau of Labor Statistics, Software Engineer employment growth is expected to grow 21 percent by 2028. Now that we’re working, studying, and socializing online more than ever, is it any wonder? Add to this the changing needs of organizations as they shift their practices into the cloud, and it’s more important than ever to have professionals who can design and maintain software to meet the needs of an organization. Whichever avenue you choose, whichever business you join or career path you follow, the full scope of work will be broad. You could be in charge of creating, developing, and maintaining a full product or just a single component of an app. Regardless of your scope of work, though, you’ll most likely be working with developers, cross-departmental staff, executives, clients, and stakeholders to mold, shape, and fulfill a design envisioned for their product. If you’re interested in the Data Science, Data Technology, Machine Learning, or Software Engineering, 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.  

Robot Companions in Senior Care Combine Computer Vision and AI

It’s 2021. Autonomous cars are no longer on the horizon. They’re here and being tested. Most businesses have shifted to a fully remote workforce or offer a hybrid option. And social activities have been redefined.  As social creatures, we humans crave attention. But does it matter from whom the attention comes?  Social distancing is a gold standard these days to keep the pandemic at bay as best we can. But what happens when the pandemic solutions affect one of the fastest growing demographics in the US?  Many active seniors have embraced the online – FaceTime and Zoom calls with friends and family, online classes for new experiences, and interactive activities to keep minds sharp. For those seniors in eldercare and assisted living, interactive has gotten a shape. Enter the robot. With Deep Learning, Computer Vision is able to enhance what a robot may see or what we see when we look into a robot’s LED face. We’ve worked hard to emulate the human experience in a machine, and have begun putting together instead a machine with human-like experience.  Unsurprisingly, robotics have become part of a variety of industries from manufacturing to construction to…eldercare? Socially Adept Robotic Companions in Senior Living Scenarios Since Jane Jetson ordered Rosey from U-Maid, we’ve wondered and worried about the roles robots might play in our lives. As we remain socially distanced and families and friends make contact through videoconferencing to those in assisted and senior living facilities, we’ve uncovered a new shortage of skilled workers. This time it’s those in the healthcare industries. Particularly those who care for the elderly. There is an ever-widening gap between healthcare workers and those who need them. In less than 10 years, there will be a shortfall of over 150,000 care workers in the US. In twenty years, that shortfall is expected to double. Recently, Robotic Researchers, Roboticists, and Data Scientists have been putting together plans for a robot much like Rosey, the maid was to Jane Jetson. Though expecting residents to only need or want help in things like delivery or picking up and delivering items, it revealed instead a desire for social interaction.  A prototype robot offers assistance from delivery to picking up items to karaoke and bingo activities. Add in a video-conferencing screen for interacting not only with friends and family members who are unable to visit, but also telehealth services with their doctor, or interacting with staff members who may not be nearby. Ways We’re Using Robots to Heal When we teach Artificial Intelligent beings and incorporate Machine Learning into our robots, we’re creating opportunities to heal. Already in use in healthcare from exoskeletons to assist stroke victims to Augmented Reality surgical practice, and real-life robotic assists in surgery, we’re able to help individuals heal physically. For many, the social isolation in eldercare homes can lead to depression and loneliness. But when someone, or rather, some thing is able to interact with them, some find a unique companion. For individuals who have difficulty connecting with people or those suffering dementia, it can be frustrating to not be able to communicate. But the role of robot in our lives just may bring a smile, a story, or a comfort. But robots aren’t just human-size companions. Some robotic companions are in the shape of pets. For those suffering from dementia, a robotic pet offers companionship and a less stressful alternative to live pets. There’s no need to worry about feeding Fido or Fluffy. These robotic pets love to be petted, but they don’t bark or meow, they don’t need to be let out, and bring to their caregivers a sense of purpose.  If you’re interested in the Data Sciences, Computer Vision, 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.  

Modelling the Mind with Computational Biology

Since Dolly the sheep was first cloned, humans have had a love-hate relationship with machines. Ok, maybe even before we asked a machine to make a living thing. In a variety of industries, machine learning systems, AI, and robotics are taking on the routine, mundane tasks once reserved for humans. But they’re doing this not to take away from humans, but to give them an opportunity to operate at a higher, creative level.  So, when you’re modelling the mind using Machine Learning and Computational Data in Neuroscience for mind blowing breakthroughs, we sit up and pay attention.  When it comes neuroscience, the benefits far outweigh the pitfalls. Just ask the researchers in China, who’ve developed a way to spot whether or not a child has autism from imaging the back of their eye. Other neurological orders such as dementia and Alzheimer’s falls under the computational neuroscience spectrum as well. From the 1970s to today, computational biology, using analytical, mathematical modelling, and simulation techniques to study behavioral and biological systems has evolved into a variety of subgenres. And it's within these subgenres we get a sneak peek into the mind of man that creates computers that can understand the mind of man. Can you wrap your head around it? Engineering the Mind – Mathematical Relationships The Life Sciences, Biostatistics, and Computational Biology all play a role in physical and mental health care. In seeking to understand the makings of the human mind, to study its syntactic rules, and to help explain how we think, human and machine have come together again. This time in the form of Computational Psychiatry. It’s here we realize our computational theories have often mirrored what we hoped to accomplish in building computers that could think with reason and logic. By understanding how we think, how the brain performs, and how it solves problems, can also help us to identify what we see as abnormalities of the mind – autism, schizophrenia, Alzheimer’s, dementia, and Parkinson’s disease just to name a few. At its heart, the fundamental message is that the brain’s way solving of inferred problems can be useful in determining hypotheses around neurological disorders.  Even within these subgenres there are varying degrees of theoretical concepts and with the data Computational Biologists and Computational Psychiatrists are able to conduct to navigate the complex inner workings of the brain. But much like the gathering, collecting, and analyzing of the data for the pandemic, the same can be done for in the mental health arena. Not the least of these theorems newly determined comes from a new theoretical model in the journal Medical Hypotheses. In it, T.A. Meridian McDonald, PhD, a research instructor in Neurology at Vanderbilt University Medical Center describes the positive traits of autism.  These positive traits she puts forth include but are not limited to increased attention, increased memory, increase differences in sensory and perception.  Building Computational Relationships Building relationships between neurobiology, environment, and mental signals in computational terms provides a cognitive model to understand the current state of one’s environment. It’s this building of relationships upon which human minds and the inner workings of the machine come together for the common good. There are positives in the negative. Mindset shifts aren’t just for learning how to work online or be more mindful, but are how best to present, and put your best foot forward. If you’re interested in Life Science Analytics, Computational Biology, 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.  

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.  

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