With over 10 years experience working solely in the Data & Analytics sector our consultants are able to offer detailed insights into the industry.
Visit our Blogs & News portal or check out our recent posts below.
Stephanie brings over 10 years of commercial business development success and technical recruitment expertise to Harnham. She has built three businesses from the ground up and specializes in exceptional delivery to customers across start-ups and large global organisations.
Stephanie joined in 2016 to head the USA business for Harnham Inc. and drive the rapid growth strategy for the region.
With over 10 years experience working solely in the Data & Analytics sector our consultants are able to offer detailed insights into the industry.
Visit our Blogs & News portal or check out our recent posts below.
We are thrilled to announce the launch of our 2019 Data & Analytics Salary Guide. With over 1,500 respondents across the USA, this year’s guide is our largest and most insightful yet. Looking at your responses, it is overwhelmingly clear that the Data & Analytics industry is continuing to thrive. This has led to an incredibly active market with 72% in the US willing to leave their role for the right opportunity. Salary expectations remain high, although we’re seeing that candidates, on average, expect 10% more than they actually achieve when moving between roles. We’ve also seen a change in the reasons people give for leaving a position, with a lack of career progression overtaking an uncompetitive salary as the main reason for seeking a change. There also remains plenty of room for industry improvement when looking at gender parity; the US market is only 23% female, falling to 17% in Data Engineering roles and 16% in the Data Science space. In addition to our findings, the guide also include insights into a variety of markets and recommendations for both those hiring, and those seeking a new role. You can download your copy of the guide here.
10. June 2019
Apartment applications. Job applications. Credit card and bank applications. We’re sharing our data today like never before and with the advent of AI and other technological advances, we’re sharing at a more rapid rate. Data breaches and unethical behaviors give us pause before we jot down our most precious information but, ultimately, there’s no stemming the tide. So, who watches out for us, the customer and the company? Enter the Risk Management Team. It All Begins with Perception In May 2018, the General Data Protection Regulation (GDPR) became law across the European Union. Its goal? To place stringent requirements on how business handles customer data. Make no mistake, however, the need and the desire is not EU-specific. It is a matter of trust and security; something customers today demand, for the most part, before signing their information away to be organized, catalogued, and analyzed. Risk teams ensure your data will be used appropriately and ensure processes for future applications. How do they do this? Risk teams need a cross-pollination of skillsets to help mitigate risk across industries. Often, risk begins in the financial sector, but it can also incorporate project management, data teams, marketing, sales, and Business Intelligence officials. And, with the advances of technology, they may also utilize Artificial Intelligence and Machine Learning to model historical data for future predictions. They must ask the right questions, ensure the right data is used for the right purpose, and validate their findings in a real-world environment. Roles of Risk Though in today’s market, everyone has a part to play, those who are focused on risk and considered part of the Risk Management Team might include the following: Chief Financial Officer (CFO) and Board Members or StakeholdersBusiness Analyst and Data Science OfficerRisk Analyst and Project ManagerStrategy and Predictive ModellerIT Marketing Together, these individuals work to challenge models, data, and decisions on behalf of customers while adhering to the company’s bottom line. Though Big Data and advanced analytics have evolved, the need to understand risks which differ in complexity, type, speed, and size remains. A few questions your Risk team might find itself asking, include: What is the impact of data and how it’s analyzed? Have we invested enough in human capital and technology, and advanced Data Analytics to focus on any potential risk including but not limited to cyber risk?Are our validations timely and appropriate? Who is responsible for decisions made by AI?Do we have the right people in place? The right tools? Are we willing and ready to challenge our data-driven and analytics-related risks?What’s our risk perspective? Do we have a good plan in place? Who will help us put one together and implement it? Ultimately, risk management in any sector, is the integration of people, processes and tools to ensure early identification and solution of risk across the enterprise. Setting the Stage or How to Get Your Risk Management Started Get buy-in from senior leadership and stakeholders as well as their commitment and dedicated participation to manage enterprise-wide risk.Make Risk Management a priority and enforce it throughout its life-cycle.Ensure technical and program management are both represented.Program management and engineering specialties should be communicated to ensure the right information is generated to help mitigate risk.Ensure risk team members, particularly those in program management, identify any concerns such as contracting, funding, costs, risks, and anything which might promote potentially dangerous ramifications if left unchecked. Even before your players are in place, you may want to consider a Risk Management Plan. Your team can help develop the parameters and implement it, but first you need to know what it is you need to watch. The CFO role in the risk team involves knowing who to pull together, what to look for, and to execute any cost-saving measures through a well-thought out plan to mitigate risk. Four Items to Consider When Creating Your Credit Risk Team As important as technological advances have become to help mitigate risk, a business still needs human capital to analyze AI decisions and offer creative solution. So, the first two items to consider when building your team may seem unusually obvious. But, the second two, may not be so clearly necessary. These included oversight and systems-wide supply chain webs of data which must be carefully tended. TechnologyHuman Capital - Get everyone on board to ensure the program’s support; Assemble the appropriate people to assess the firm’s risks; Educate your team; Set your risk level.Supply Chain - Globalization has made companies’ supply chains more vulnerable than ever. Risk Governance - Conduct a SWOT analysis (Strengths/Weaknesses/Opportunities/Threats) to help engage your company members at every level as subtly work in broader educational efforts. Want to help the 99% have access to funds they need to live the lives they want? We may have a role for you. Take a look at our latest opportunities get in touch with one of our expert consultants to find out more. For our West Coast Team, call (415) 614 - 4999 or send an email to firstname.lastname@example.org. For our Mid-West and East Coast Teams, call (212) 796 - 6070 or send an email to email@example.com.
28. March 2019
If you’ve applied for a credit card or loan recently, you’ll be aware of the swift response you now receive. No human can crunch the numbers and make the determination that fast, right? Although big banks are now adopting Big Data, Machine Learning, and AI into their legacy processes, startups have been disrupting the sector for a few years now. As banks and credit unions scramble to keep up, Fintech innovation is bringing together machine language, analytics, and AI to help form Big Data decisions in the industry. The forward-thinking potential of these technologies has led to some real-world uses to combat fraud, offer access to alternative data sources, and suggest real-time analysis for risk. So, Robots are Determining My Credit Risk? Well, yes and no. Often, those in the financial sector are using AI to assess Credit Risk. What once required Risk Analysts to determine manually, is now done in a matter of seconds with an early warning system developed by ING, PwC, and Google. This AI-powered system helps analysts make faster and more informed decisions about potential risk. How do they do this? Using pre-set criteria, they can gauge and analyze risk based on parameters such as whether or not a client has negative media coverage or if a share price falls below a certain percentage. If the world today is based on perception, even such items as bad reviews, negative coverage, and lower than average share prices can affect determinates. In addition, having these parameters can also help determine best practices and how businesses and individuals can be given opportunities outside the scope of big bank processes. However, as data breaches continue to mar profiles of both individuals and business, Machine Learning components offer platforms the chance to stem the tide of negativity. How Machine Learning Helps Prevent Fraud This is a simple process which requires two key measures. The first is to feed the machine not just a large amount of data, but knowing the parameters set, so the machine is fed relevant information. The second is human input which gives the machine its parameters to operate by. From there, the software will take the information, gain an understanding of the data patterns, and identify any signs of fraud. If done well, the automation process will employ solutions without sacrificing quality. Machine Learning in Determining Scorecard Models Alternative data sources offer more options not only to banks and credit unions, but also to borrowers. Using Machine Learning creates a more flexible, robust model when it comes to the type of information most useful to various borrower profiles. Having profiles prepared allows for automated scorecard updates and can generate better responsiveness and intelligence of a borrower’s risk profile. This process can be empowering for both startup and big bank tech. The Matured State of Analytics Though humans must initially input parameters, the benefits of Machine Learning using a decision engine can dig deeper and reach farther than ever before. This type of platform can gather a variety of scenarios across the industry and can constantly analyze the information, helping inform the processes of setting credit limits, loan origination, and risk-based pricing. As an extension of a modern analytics platform, these processes fill in the gaps where other platforms may lack the data or programming required to run effectively. But, as these platforms mature, they are helping to drive innovation throughout the Fintech industry and shaking up the outdated, cumbersome processes of old for a much more streamlined efficient operation. Want to inform decisioning and work with data engineers to build validation frameworks? Are you looking to get in on the ground floor of a startup opportunity in the Fintech industry? If so, we may have a role for you. If you’d like to learn more, check out our current vacancies or contact one of our expert consultants to learn more. For our West Coast Team, call (415) 614 - 4999 or send an email to firstname.lastname@example.org. For our Mid-West and East Coast Teams, call (212) 796 - 6070 or send an email to email@example.com.
21. March 2019
Black Friday. Cyber Monday. Tech Tuesday? The weekend surrounding Thanksgiving is full of opportunities to save big. This week sees even more action at the two-day AI and Big Data Conference in Santa Clara, California. Though LinkedIn may show news of Silicon Valley upsets, no one has told these thought leaders, forward-thinking brands, and hot start-ups as this conference is expected to be the biggest yet. In the spirit of the season, we thought we’d hone in on building a foundation for your digital transformation as you look to the new year. Lay the Foundation With AI at the heart of modern applications in today’s business world, it’s important to not only have digital leaders who can take the reins, but also, data scientists who are pivotal developers. These are the individuals who have mastered the tools and skills of data science. They can understand and translate the data gathered via machine learning and AI for such common applications as predictive analytics, consumer experience, and image-based search. To create an effective AI pipeline, developers need a place to store, manage, and control models as part of the DevOps lifecycle. In addition, they’ll need a data lake to store, aggregate, and prepare data for exploration, predictive modelling, and training. Like so many technologies of today, DevOps is part of an integrated collaboration environment, and is the baseline from which all pipeline functions emanate. Things to Consider as You Build Your AI Strategy Artificial Intelligence (AI) has been a buzzword for a number of years, but as many businesses are quickly coming to know, it’s important to have the right strategy, and that includes knowing when to apply it to solve business problems, and when not. Here are a few things to think about as you plan: Ask what problem you want AI to solve. Think it through. Identify where it can be most effective and understand that it is not a solution for everything. It’s a huge investment, so if there are other ways to solve your problem, identify those solutions first. Do your research. Consider the legal aspects as you analyze and set a benchmark for industry trends. Have a solid understanding of analytics. If you’re using AI in your business strategy, make sure you understand your data in order to either implement it successfully, or know enough to pull the plug. Educate Your Team by Including them in the transformation. Remind them it’s not about machines taking over their jobs, but that it’s an opportunity to grow. Offer opportunities for upskilling, and education. Trends in Transformation If your company wants to stay ahead of the competition, now is the time to embrace the technology of the future. Create an immersive customer experience, pair your analysis with machine learning, and get comfortable with experimentation in support of your organization’s goals. We’re looking forward to being inspired by the thought leaders and new tech evangelists at this week’s AI and Big Data Expo, discovering how businesses are using artificial intelligence, machine learning, and data analysis to find new ways to engage and improve their customer experience. If you’re interested in Big Data and Analytics, we may have a role for you. We specialize in junior and senior roles. If you’re attending the Big Data and AI Expo in Silicon Valley, November 28 and 29, stop by our booth and say hi. We look forward to meeting you and can discuss opportunities on the spot. If you can’t make it, you can check out our current vacancies or contact one of our recruitment consultants to learn more. For our West Coast Team, call (415) 614 4999 or send an email to firstname.lastname@example.org. For our Mid-West and East Coast Teams, call (212) 796 6070 or send an email to email@example.com.
27. November 2018
We are thrilled to announce the release of the 2018 editions of our market-leading Salary Guides for the UK, US and Europe. Having spoken to thousands of Data & Analytics professionals across the globe, we gained invaluable insights into key industry salaries and trends across a wide variety of specialisms and sectors. Our surveys are created for analysts, by analysts, and offer a detailed, on-the-ground look at what’s concerning talent in the industry. As with the last few years, 2018 has shown us that the data industry continues to grow and shows no sign of slowing, with demand for analysts still easily outstripping supply. You can download our US Salary Guide here, including salary and trend analysis across five key specialisms: Data & Technology, Data Science, Digital Analytics, Marketing & Insight, and Risk Analytics.
10. September 2018
Boston is a thriving metropolis of music, movies, and industry. It works hard and it plays hard. And on the first of May, it will be the site of the Open Data Science Conference East (#ODSC). For four days, thousands of aspiring and professional data professionals will converge to learn about trends in the industry, network, hire for and find employees. Traditional hiring methods don’t work here, the competition is fierce, and the demand is high.From virtual and augmented realities to embedded video on your resume, we offered a glimpse into trends in today’s hiring market. Last week, we talked about how jobseekers can market themselves. This week, we’ll take a deeper dive into one of those topics you can use to help boost your resume. Embedded video.Reasons to Embed a Video in Your ResumeIt adds a level of depth to the traditional resume while giving insight to the hiring manager about you as a person. Instead of ‘don’t judge a book by its cover’, you can imply ‘don’t judge a candidate by a piece of paper’.It gives you a chance to really shine by not just highlighting, but showing, your achievements.Not only does the video resume offer a glimpse into your personality and skills, it also caters to both listening and visual style preferences.Four Areas of Focus for Your VideoThough the traditional resume may be on its way out, the information is still viable and can serve as your “script” to help you plan your video sequence. However, along with script are three other areas of focus to consider such as appearance, technology, and distribution. Together, these four areas of focus set the framework as you plan your video resume.Appearance It takes less than ten seconds to make a first impression and that’s before a word has been spoken. A good rule of thumb is to dress professionally (solid colors are better than patterns), make sure your lighting is good, smile, and speak clearly.Script Whether you’re embedding your video into your resume or your resume is your video, you’ll want to have a script. A one-page script is enough. With it, you can outline what will happen in the video such as whether or not the recruiter will see you or a slideshow of your work. It can also keep you on track and focused as you highlight your various projects and achievements. Here are a few tips to get you started:Explain why you’re the best person for the job.Research the company, if possible, and show how your skills and expertise can help them solve their problems.Keep your video short. Anywhere from a 30-second elevator pitch to a 2-minute in-depth video. Not only will recruiters and hiring managers gain insight into you as a person, but they’ll get a first-hand look at your technical skills and creativity.TechnologyThough most mobile phones have the capability, if you’re going to go the extra mile, go for higher quality with a digital camera. Besides higher quality, a digital camera offers stabilization by using a tripod. Then from either a mobile phone or digital camera, your video can be uploaded into video editing software such as iMovie or MovieMaker available on your computer.DistributionLast, you’ll choose your distribution method such as YouTube or Vimeo. Now you have a link to embed anywhere or send to anyone.In the world of digital and analytics, the focus is often on the customer. Insight jobs help businesses solve complex business problems. Data professionals figure out what it is the customer needs and wants through engagement, traffic conversion, and so on. But, in the world of recruiting, the customer is you. The candidate.Want to show off your predictive modelling and marketing skills for a household name in media entertainment? We’re hiring for a Lead Marketing Scientist in the Greater Boston area. In this role, you’ll be seen as a voice of influence delivering key insights and recommendations from ground level staff to C-level stakeholders.Harnham specializes in Junior and Senior Data and Analytics roles, check out our current vacancies or contact us to learn more.For the East Coast team please call 212-796-6070, or email firstname.lastname@example.org.
03. April 2018
Why Texas is the place to be for technology jobs The big data market is heating up the world over, and perhaps no more so than in Texas. The Dallas, Austin and Houston areas in particular are experiencing a massive boom in big data jobs, with many large tech companies making the move from Silicon Valley to enjoy all that Texas has to offer. But why the shift towards the southern state, and what does it mean for candidates looking big data jobs and broader technology roles? Tax-free Texas The Texan market is looking increasingly lucrative for both young start-ups and established tech companies alike. One of the most significant factors in this rapid growth is the favourable tax conditions in the state. There’s no corporate or individual income tax, with Texas ranking 47 out of 50 states when it comes to taxes paid per $1,000 of personal income. As California tax rates hitting up to 10.84 for corporations and 12.3% for individuals, it’s understandable that entrepreneurs and big business alike are looking to the southern state for bigger breaks on tax day. On top of this, Texas offers favourable funding and regulatory conditions for young and growing businesses, providing a ‘pro-business’ environment for corporations to thrive. Texas State offers billions of dollars in incentives to businesses every year, providing all the more reasons for those in the technology industry to think hard about making the move. With a state government that celebrates business and provides easy to navigate laws and regulations, many businesses find the transition from Silicon Valley to Austin smooth and seamless. As organisations in San Francisco are priced out of the area, some of the nation’s top talent are moving to pastures greener – and for many, that means Texas. The living is easy On top of the tax breaks gained when moving to Texas, many movers and shakers experience a favourable quality of life. The cost of living is low – for example, the median home value in Austin is $321,600 compared to San Francisco’s $1,1943,300 – with relatively cheap utilities and the second-largest GDP in the nation. The market is robust, which has resulted in money being poured back into cities and communities to make them more attractive to businesses and young families. People can move to Austin and get more bang for their buck than they can in many other parts of the country, enjoying not only a booming technology market, but also superior housing and affordable living. Add in a comfortable climate and famously friendly locals and you’ve got a part of the country that is becoming increasingly appealing to even the most seasoned technology professionals. Technology is taking off Texas is huge when it comes to the technology industry. There was a 41.4% jump in technology industry employment between 2001 and 2013, resulting in large numbers of jobs being taken up across Austin and the wider state. And in 2016 alone, Texas added a huge 11,000 new technology jobs to its market, ranking it second of the 50 states in tech industry employment. The tech hub of Austin alone is home to employers such as Dell, Apple, Microsoft and Samsung, plus an increasingly significant number of start-ups peppering the landscape with innovation. There are a range of incubators and universities that feed into the city’s talent pool, with Austin ranking third in the list of US cities providing the most technology jobs in 2017. However, such growth doesn’t stop Austin and its other Texan counterparts from being a friendly and accessible place to work. There is less of the cut-throat nature that comes with tech in Silicon Valley, and more of a community, collaborative approach. Meanwhile, Dallas-Fort Worth is enjoying being the second-largest data center market in the country, offering an abundance of big data jobs to savvy business people. Working in Texas Much of the Texas technology market is geared towards candidates currently, with more jobs than skilled employees to fill them. Companies are doing more to attract top talent to Texas, including offering generous benefits packages, relocation allowances and flexible work conditions, and the expectation is that this market will only continue to grow. If you’re looking for technology jobs in Austin or further afield in Texas, we might have just what you’re looking for. Take a look at our US data and technology jobs here.
05. July 2017
A survey suggests that the terms "hard-working", "team player" and "motivated" are so ubiquitous in résumé's that they have become utterly meaningless. But what might you write instead, asks Finlo Rohrer.It's not easy to write the covering letter that goes with résumé's. You know it's going into a massive pile that will leave some poor recruiter dead-eyed in a supremely bored fugue. The sentiments you want to express are not just samey, they can even be counterproductive. Simply stating you're "creative" does seem rather to show the opposite.Perhaps you should adopt the old journalistic adage of "show me, don't tell me". As an old journalism professor once said: "Don't start a sentence with 'interestingly…'. Let the reader be the judge of that." If having described a feat you have to say it is "spectacular" either a) you're not very good at describing feats or b) the feat really wasn't that spectacular."Everyone you've ever met talks about themselves as a 'people person' and says they can 'work independently as well as part of a team'," says Corinne Mills, managing director of Personal Career Management.As well as creative, there are other lightly dished-out terms that are counter-productive. "Too many people say they are an 'excellent communicator', quite often in a poorly written résumé with spelling errors."Candidates need to be honest and truthful, argues Claire McCartney, resourcing and talent adviser at the Chartered Institute of Personnel and Development. "They need to back up what they are saying rather than giving out cliches. Give real examples around your achievements, anything that makes you stand out. Include things you are passionate about." We're back to show rather than tell.A person might be exceptionally hard-working, says Mills. "Hard working might be 'finishing a project with extremely tight deadlines required me to work at weekends to get it finished'. That gives me some evidence about your conscientiousness."So avoid cliches, tailor your list of achievements to the job description but don't tell outright lies. If the truth is winkled out during the interview, you'll never get the job. Well, almost never.Click here for the article on the web.And be sure to check out our Résumé Tips articles updated regularly.
21. January 2015