Challenge: The checklist of desirable attributes in a data scientist include a creative and well spoken systems architect, quantitative analyst, software engineer, and business analyst that's practiced in data integration and data visualization. So it's no wonder the data scientist is the unicorn of the industry. It also explains why firms have found it almost impossible to hire one, and apparently just as difficult to keep one from being poached.
Why it's important: Still, as investment in big data grows, and as big-data analysis becomes more important for competitive advantage, it is critical to find data analysts proficient enough to use the technology, generate reports, and deliver insights. McKinsey Global Institute estimated that by 2018 there will be 4 million big-data-related positions in the US and a shortage of up to 190,000 data scientists. There’s also a need for folks who aren't quite full-fledged data scientists, but are data savvy nonetheless.
Wall Street & Technology's Capital Markets Outlook 2015
Here are 10 topics that will be a focus for financial institutions in 2015 and beyond:
- Technology Innovation Returns to Financial Services
- Global Banks Need to Demonstrate RDA Progress in 2015
- Where Should You Spend Your IT Budget in 2015?
- Financial Firms to Struggle With Growing Social Infrastructure in 2015
- As Market Matures, Fintech Startup Winners Will Emerge in 2015
- Universities Increasing Programs for Data Scientists
- Next Year, Aim for Communication & Clarity of Cloud Apps
- E-Trading Disruptors Seek Untapped Liquidity in Corporate Bonds
- Swap Markets Debate Anonymous Trading in SEFs
- The Clock For Market Structure Change Is Ticking
- Increasing Cyberthreats Pose Massive Challenge for Financial Firms
Where the industry is now: Fortunately, universities are helping to turn out a greater number of data scientists. Last year, only a few schools offered degrees that focus on data scientist. Today there is a broader selection, with more universities looking to offer similar programs. Many are launching in January of 2015.
Stevens Institute of Technology recently announced its own data-science curriculum, Financial Services Analytics, starting in January 2015 in collaboration with Accenture. Dinesh Verma, professor and dean in the School of Systems and Enterprises at Stevens, says that, due to the high salaries and high demand for data scientists, it quickly became a popular program amongst undergraduate and graduate students. "Financial engineering has been one of the fastest growing on campus," says Verma, "It's not hard to attract high-quality students to the financial analytics program."
[Read more about data science education: Big Data Analytics Master's Degrees: 20 Top Programs.]
To be a data scientist candidate, students should come to the table with some experience in programing, statistics, and design. But it's not all technical -- all curriculums are focused on teaching a mix of theory and practice, so an ideal candidate has business acumen and passable communication skills.
Focus in 2014: Although many academic programs are being launched, the key to success is which programs are able to strike a proper balance between theory and pragmatic utility. It's one thing to have a course that says here is a technique for a certain tool, but that falls into the area of training.
Educational programs are trying to give students exposure to fundamental aspects of statistics, even teaching them how to learn and look out for new technologies to fit into what they're attempting to do. These programs also teach students to look at notions of variables, how to ask the questions, and to know what variables might suggest what data needs to be collected. “It’s a bit of top-down and bottom-up,” says Verma. “You want to know what questions to ask that suggest what data to go looking for.”
Verma adds that programs are seeking people with nuanced understanding of domain that perhaps have the emotional intelligence to know what questions matter, and what decisions need to be made in better ways than in the past.
Industry leaders: Many of the world’s top business schools are offering or planning to offer courses in data mining, statistics, and data visualization. Stevens University is joining such institutions as Columbia University’s Fu Foundation School of Engineering and Applied Science; the University of California at Berkeley, which offers a master of information and data science; and Stanford, which offers online courses for data mining and statistics.
Price tag: Due to the pace at which technology is changing, technical training will soon become stale. Verma says graduates will find themselves returning to the classroom to retool with a graduate certificate or a master's program as needed in their career.
Many professionals who seek to upskill their competencies to today’s technology study in the evening, using full or partial corporate tuition reimbursement plans. Some companies sponsor dedicated company cohorts for graduate studies in critical skills areas.
Given the hard schedule of today’s professionals in the financial services industry, a good estimate for professional development/education that most professionals can reasonably schedule is about two courses annually at a total cost of about $8K-$10K. Most progressive organizations support their employees in this regard.
“We've truly entered realm of lifelong learning,” adds Verma. “To not have some element of continued education would be a mistake.”Becca Lipman is Senior Editor for Wall Street & Technology. She writes in-depth news articles with a focus on big data and compliance in the capital markets. She regularly meets with information technology leaders and innovators and writes about cloud computing, datacenters, ... View Full Bio