AI News, Frequently Asked Questions
- On Wednesday, June 6, 2018
- By Read More
Frequently Asked Questions
The demand for data scientists is growing exponentially [1, 2] and IBM estimates that by 2020, the number of jobs for US data professionals will increase by 364,000 openings to 2,720,000 .
Washington DC, with a high concentration of both corporate and government employers, has emerged as a hotspot for data science, with large corporations drawn to its highly skilled talent pool.
Data Scientist: The Sexiest Job of the 21st Century
When Jonathan Goldman arrived for work in June 2006 at LinkedIn, the business networking site, the place still felt like a start-up.
For one thing, he had given Goldman a way to circumvent the traditional product release cycle by publishing small modules in the form of ads on the site’s most popular pages.
Through one such module, Goldman started to test what would happen if you presented users with names of people they hadn’t yet connected with but seemed likely to know—for example, people who had shared their tenures at schools and workplaces.
Goldman is a good example of a new key player in organizations: the “data scientist.” It’s a high-ranking professional with the training and curiosity to make discoveries in the world of big data.
If your organization stores multiple petabytes of data, if the information most critical to your business resides in forms other than rows and columns of numbers, or if answering your biggest question would involve a “mashup” of several analytical efforts, you’ve got a big data opportunity.
Much of the current enthusiasm for big data focuses on technologies that make taming it possible, including Hadoop (the most widely used framework for distributed file system processing) and related open-source tools, cloud computing, and data visualization.
Greylock Partners, an early-stage venture firm that has backed companies such as Facebook, LinkedIn, Palo Alto Networks, and Workday, is worried enough about the tight labor pool that it has built its own specialized recruiting team to channel talent to businesses in its portfolio.
“Once they have data,” says Dan Portillo, who leads that team, “they really need people who can manage it and find insights in it.” If capitalizing on big data depends on hiring scarce data scientists, then the challenge for managers is to learn how to identify that talent, attract it to an enterprise, and make it productive.
In a competitive landscape where challenges keep changing and data never stop flowing, data scientists help decision makers shift from ad hoc analysis to an ongoing conversation with data.
More enduring will be the need for data scientists to communicate in language that all their stakeholders understand—and to demonstrate the special skills involved in storytelling with data, whether verbally, visually, or—ideally—both.
But we would say the dominant trait among data scientists is an intense curiosity—a desire to go beneath the surface of a problem, find the questions at its heart, and distill them into a very clear set of hypotheses that can be tested.
As Portillo told us, “The traditional backgrounds of people you saw 10 to 15 years ago just don’t cut it these days.” A quantitative analyst can be great at analyzing data but not at subduing a mass of unstructured data and getting it into a form in which it can be analyzed.
A data management expert might be great at generating and organizing data in structured form but not at turning unstructured data into structured data—and also not at actually analyzing the data.
Several universities are planning to launch data science programs, and existing programs in analytics, such as the Master of Science in Analytics program at North Carolina State, are busy adding big data exercises and coursework.
The Insight Data Science Fellows Program, a postdoctoral fellowship designed by Jake Klamka (a high-energy physicist by training), takes scientists from academia and in six weeks prepares them to succeed as data scientists.
As one of them commented, “If we wanted to work with structured data, we’d be on Wall Street.” Given that today’s most qualified prospects come from nonbusiness backgrounds, hiring managers may need to figure out how to paint an exciting picture of the potential for breakthroughs that their problems offer.
One described being a consultant as “the dead zone—all you get to do is tell someone else what the analyses say they should do.” By creating solutions that work, they can have more impact and leave their marks as pioneers of their profession.
As the story of Jonathan Goldman illustrates, their greatest opportunity to add value is not in creating reports or presentations for senior executives but in innovating with customer-facing products and processes.
At Intuit data scientists are asked to develop insights for small-business customers and consumers and report to a new senior vice president of big data, social design, and marketing.
New conferences and informal associations are springing up to support collaboration and technology sharing, and companies should encourage scientists to become involved in them with the understanding that “more water in the harbor floats all boats.” Data scientists tend to be more motivated, too, when more is expected of them.
The challenges of accessing and structuring big data sometimes leave little time or energy for sophisticated analytics involving prediction or optimization.
People think I’m joking, but who would’ve guessed that computer engineers would’ve been the sexy job of the 1990s?” If “sexy” means having rare qualities that are much in demand, data scientists are already there.
In those days people with backgrounds in physics and math streamed to investment banks and hedge funds, where they could devise entirely new algorithms and data strategies.
One question raised by this is whether some firms would be wise to wait until that second generation of data scientists emerges, and the candidates are more numerous, less expensive, and easier to vet and assimilate in a business setting.
Why not leave the trouble of hunting down and domesticating exotic talent to the big data start-ups and to firms like GE and Walmart, whose aggressive strategies require them to be at the forefront?
If companies sit out this trend’s early days for lack of talent, they risk falling behind as competitors and channel partners gain nearly unassailable advantages.
The quant crunch: The demand for data science skills
In 2011, McKinsey published the report Big data: The next frontier for innovation, competition, and productivity which made significant workforce projections and said that by 2018 “140,000-190,000 more deep analytical talent positions, and 1.5 million more data-savvy managers are needed to take full advantage of big data in the United States”. This report, along with a litany of data scientist focused articles such the Harvard Business Review article in 2012 titled Data Scientist: The Sexiest Job of the 21st Century by Thomas Davenport and DJ Patil, played key roles in driving awareness and action by educators to create new data science programs.
Complementary data roles such as chief data officer, data engineer, and data governance professionals have also been largely ignored by academia and upstarts. In 2016, IBM in partnership with the Business-Higher Education Forum commissioned Burning Glass Technologies to take a deep look at the data savvy professional job market in the United States. We divided the job role categories into 6 broad areas shown in the table below.
Burning Glass collects millions of online job postings from more than 40,000 sources and applies patented technology to deduplicate, mine, and code detailed data from each posting describing the specific skills, education, experience, and work activities required for the job – going well beyond the occupation and industry codes offered in other sources.
What is the salary of a data scientist?
Since there is a huge demand of the job role but less supply of skilled data scientist, most product based companies and startups are hiring data scientists having the skills in these technologies and are willing to pay them a package of 6 LPA, some have even said to scale up to 10 LPA as freshers.
If you’re planning to start your career in analytics and data science, you could apply to these companies where you will be able to learn these skills at a very early stage giving you hands on experience.
Salaries state wise in India: Now, since you already have an idea of what skills pays the most lucrative salaries, I suggest you could start working on your skills in these technologies and be prepared before you could apply for jobs.
This will give a very positive impact to the recruiters looking to hire a candidate, since most of them are looking for people who have the talent and practical skills in these technologies.
Department of Mathematics Statistics
Career Services for math majors will now be handled mainly at the college-level (CNS). See the new CNS Career Services webpage. Students can make appointments with the professional advisors using SSC or drop-in to meet with a peer advisor. Of particular interest on the webpage are new tools to help you hone your interview skills. Check out the internships that they post on their webpage.
Located in 511 Goodell, Career Services offers counseling on resume writing and interviewing, coordinates on-campus job fairs and interviews, and keeps extensive listings of job openings and advertisements for all fields and majors.
Whereas in the past advanced mathematics was generally restricted to the physical sciences and engineering, today there is an ever growing demand for mathematical expertise in the biological and social sciences, as well as in finance and business management and the burgeoning field of data science. Every student should carefully consider the following five points when deciding on a course of studies during the undergraduate major.
In the course of his or her undergraduate studies, each student will naturally develop some preferences for the various subfields of mathematics or statistics, and those interests will largely determine the student's choice of concentration within the major.
While there is no fixed list of occupations that follow from a major in mathematics or statistics, the most common career paths of graduating students fall into some broad categories.
Besides good command financial markets, tax and insurance law, regulatory requirements, accounting, and so forth, an actuary must have solid background in applied mathematics and statistics.
mathematics major can launch a career in the wide-ranging world of information technology and computing services, provided that the major studies are complemented by enough training in computer science.
A major in mathematics that includes statistics, augmented by a minor in computer science and courses in economics, accounting, finance, or industrial engineering, for example, would provide a solid basis for a business career.
Some of the many resources on the web include: http://www.quantnet.com/http://www.quantfinancejobs.com/https://www.cfainstitute.org The problem solving and critical thinking skills possessed by mathematics and statistics majors make them very desirable candidates for positions with consulting firms.
These positions are accessible with a bachelor's degree, but they require a quick and adept mind that combines quantitative expertise with business acumen and excellent communication skills.
Mathematics majors wishing to obtain the intermediate equivalent of the Massachusetts certification to teach mathematics at the middle or high school level must: Any student who is interested in becoming a middle or high school mathematics teacher should contact the Secondary Teacher Education Program.
The Commonwealth's Standard I Subject Matter Knowledge for mathematics states: 'The effective teacher of mathematics has completed the college's or university's requirements for a major in mathematics, or the equivalent, by demonstrating knowledge of: mathematics, including: algebra, geometry, analytical geometry, trigonometry, calculus, number theory, probability and statistics, and the history of mathematics;
Statistics is in the process of developing courses specifically geared to future secondary mathematics teachers, especially in light of the Common Core State Standards in Mathematics (http://www.corestandards.org) and in light of the recommendations of The Education of Mathematics Teachers I and II, Conference Board of the Mathematical Sciences, published by the American Math Society, 2001 and 2012 (available from http://cbmsweb.org/MET_Document/).
The office offers counseling on resume writing and interviewing, coordinates on-campus job fairs and interviews, and keeps extensive listings of job openings and advertisements for all fields and majors.
The 'Minuteman Mentors' program allows a student to contact registered alumni who are employed in the field of the student's interest for the purpose of consultation and general advice about job opportunities in that field.
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