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.
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 firstname.lastname@example.org. For our Mid-West and East Coast teams contact us at (212) 796-6070 or send an email to email@example.com.
18. February 2021
At the beginning of every year and particularly the start of a new decade, we often find ourselves reassessing our priorities. Though this year was no different, it does have the twist of a pandemic. Businesses and individuals were forced to pivot toward a new normal. Together, we’ve moved quickly and one thing this year’s Salary Guide has shown us is that priorities have changed. In previous years, focus was on higher salaries and it was expected to stay in a position only two or three years before moving on to the next job. But this year, stability is the name of the game. And so, priorities shift. Candidates now want to stay in a role that could lead to career progression. What’s Changed? In the Data & Analytics industry, flexible working options have steadily increased, though it was already a way of life for many. Add into the mix, the increased need to work from home for employee safety or in controlled environments for those whose role did not allow for remote working such as those in the life sciences. Financial considerations were no longer top dog in hiring and retaining top talent. Longevity, career progression, and good management are highly desired. When everyone is online and flexible working options are the new normal, it’s important to have strong leadership. Four Future Changes to Come With the world online, working, and learning from home, bandwidth has become a non-renewable resource. Too much traffic. Too many people online could cause issues particularly during prime working and learning hours. Though with everything online, what does it mean to have prime hours now? Setting Priorities – Just because you’re working from home doesn’t mean you should lock yourself in your office for hours on end. Set aside time for food, family, and fun. Elevate the Home Office - Larger, more stable devices may see a resurgence. The home office is truly just that with the standard desktop and monitor to more easily see information. For those in many industries, two screens really help set the tone. Flexible Shopping Options are Here to Stay – When you’re working and learning from home, time is of the essence. The benefits of delivery, pick-up, and even some more expanded food centers could change the way we eat and gather. Retail is being redesigned for the new normal.Logistics of Social Distancing meet Machine Learning – As we focus on social distancing, mobile applications may shift toward a more logistics focused future using crowdsourcing and Big Data. From contact tracing to food buying, it will be important to have technologies that can keep up with people at all hours of the day and night to deliver goods and services. In our recently released 2020 Salary Guide we discuss each specialism, what’s working and what isn’t. And how businesses can hire and retain top talent to keep their projects on track and their businesses running smoothly. If you’re interested in Data and Technology, Risk or Digital Analytics, Life Sciences Analytics, Marketing and Insight, Data Science, or Computer Vision, take a look at our current vacancies. If you’d like to learn more, get in touch with one of our expert consultants. For our West Coast Team, contact us at (415) 614 - 4999 or send an email to firstname.lastname@example.org. For our Mid-West and East Coast teams contact us at (212) 796-6070 or send an email to email@example.com.
27. August 2020
COVID-19 has reshaped the way we do business, how we interact with each other, closed and opened opportunities. Essential workers are on the frontlines and scientists work feverishly in the background to help flatten the curve and find a cure. The Life Sciences industry has seen a surge in demand, but can those needs be met in time? New York, California, and Boston, face the highest demand and the biggest shortage of workers to fill the jobs. In Massachusetts alone, it’s estimated that though 74,000 people filled Life Science jobs by the end of 2018, there would be a need for an additional 12,000 by 2024. This was before the pandemic struck. The need is ever greater now. So, what skills do you need to enter the Biotech and Life Sciences field and if you’re in the field, how can you upskill or reskill to fill the most in demand roles? THREE ADVANCED SKILLSETS FOR A POST-PANDEMIC WORLD Computer Vision – A subset of AI, Computer Vision can help the healthcare industry in a variety of ways. It can help identify anomalies in x-rays, help craft prediction models for things like tracking and vaccine solutions, and enhance technology workflows. Data Storytelling – One key element businesses look for in a Data professional is someone who has good data storytelling skills. The ability to translate complex numbers and statistics into something executives and stakeholders can understand is becoming ever more important and ensures sustainability of business continuity. Not only does Data Storytelling make information more digestible for non-technical professionals, it also helps business leaders to make powerful insights about where they are and what steps they need to make moving forward.Skills in Healthcare Technologies – Healthcare technology skills are in high demand. Data professionals who can use and understand medical data in real-time to get results will be highly sought after. Advanced skill sets in healthcare, biotechnology, and similar areas within Life Sciences will see a surge in demand and would be most relevant to companies now more than ever before. Computer Vision, Data Storytelling, and Healthcare Technology skills have become three of the top skillsets needed for today’s world. Each one feeds to the other, and as important as technical skills are, it’s just as important to have soft skills. Especially now. Thankfully, both soft skills and technical skills can be taught. But there still exists a gap between school and business. Below are some ideas on how to bridge that gap. BRIDGING THE GAP BETWEEN SCHOOL & BUSINESS STEM and STEAM skills will be in higher demand now more than ever before. As important as it is to ensure students with the desire to move into these fields, it’s more important to begin with the schools. For the professionals already in the industry, there are other ways to encourage bridging the gap. Draw more students into STEM programming careers and sustain encouragement as they progress in their studies and career.Emphasize skills with a focus toward the life sciences field.Emphasize that students don’t have to choose a business career over a science career. There is crossover leading to more opportunities.And for those life long learners (read: already in the field), ensure opportunities for professional development.Find talent in other creative ways. Consider ‘non-traditional’ candidates. Business processes have shifted online, looking for your next job has become more daunting than ever before. But here’s the good news. Everyone’s on the same page. Leaders, hiring managers, recruiters, and prospective employees are all navigating a new way of doing business and finding talent to keep those businesses running. In the wake of work-from-home policies, remote working, and the shifting landscape of working outside the office, technology, and particularly biotechnology careers are prime opportunities to both gain increased knowledge in your chosen field or begin your career path. If you’re interested in Big Data & Analytics professional opportunities, 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 firstname.lastname@example.org. For our Mid-West and East Coast teams contact us at (212) 796-6070 or send an email to email@example.com.
04. June 2020
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