Data Scientist

data-scientist-trainingData Scientists analyze business data for actionable intelligence.

Data scientists mine and analyze data from a range of sources, including customer transactions, click streams, sensors, social media, log files and GPS plots. Their mission is to unlock valuable and predictive insights that will influence business decisions and spur a competitive advantage.

The data explosion – fueled by increased bandwidth and processing power, innovative data analysis tools, and the proliferation of inexpensive cloud-based storage solutions – has placed Data Scientist among the most demanded and lucrative IT careers. Data scientists’ salary and demand are well-deserved, as their findings have the potential to make or break the business. To illustrate this point, a 2011 study from the McKinsey Global Institute indicates retailers that maximize data analysis capabilities could increase profits by a whopping 60%, while the health care industry can reduce operational expenses by 8% - that’s $200 billion per year.

The most successful – and sought after – data scientists possess that rare combination of analytical skills, technical prowess and business acumen needed to effectively analyze massive data sets while thinking critically and shifting assumptions on the go, ultimately transforming raw intelligence into concise and actionable insights.

What about BIG DATA? The main difference between “big data analysis” and “data analysis” is that big data sets are beyond the threshold of typical database management systems. Due to its massive size and heterogeneous structure, big data is often rendered visually, as a heat map or tree map for example, allowing big data scientists to identify, analyze and present complex patterns that would otherwise remain hidden.

a.k.a. Data Architect | Data Analyst | Big Data Scientist | BI Analyst | BI Engineer | Data Mining Engineer

Data Scientist Training

Data Scientist Skills & Responsibilities

Typical day-to-day activities and in-demand skill sets for Data Scientists include:

  • Perform data-mining, modeling and hypothesis generation in support of high-level business goals.
  • Stay current with emerging tools and techniques in machine learning, statistical modeling & analytics.
  • Successful data scientists often have strong aptitudes for business, technology, mathematics & statistics.
  • Need strong oral & written communication skills to present data as a concise story for diverse audiences.
  • Big data scientists develop customized algorithms to solve analytical problems with incomplete data sets.
  • Big data scientists often use data visualizations, e.g., heat maps, to analyze and present complex trends.
  • Many data scientists use Hadoop - an open-source Apache framework - to analyze & mine big data sets.
  • Some data scientists have computer programming skills – such as SQL, Python, Unix, PHP, R and Java –
    which they use to modify or develop custom analytical solutions.
  • Data scientists often work in a team setting, with managers, IT administrators, programmers, statisticians,
    graphic designers, and experts in the company’s products or services.


Data Scientist Salary

  • Mean annual salary for data scientists in North America: $121,000

Data Scientist Salary $121,000


Salaries for data scientists and related positions:

  • Business Analyst: $78,000
  • Business Intelligence Analyst: $84,000
  • SAS Data Analyst: $84,000
  • IBM Data Analyst: $84,000
  • Data Mining Engineer: $93,000
  • Machine Learning Engineer: $94,000
  • Big Data Scientist: $97,000
  • Data Architect: $107,000
  • Business Intelligence Architect: $110,000
  • Enterprise Data Architect: $110,000
  • Big Data Architect: $111,000
  • Hadoop Engineer: $112,000
  • Data Warehouse Architect: $113,000
  • Data Scientist: $121,000
  • Senior Data Scientist: $130,000
  • Senior Big Data Analyst: $138,000

The business intelligence & analytics field has practically unlimited earning potential. Talented data scientists with a solid education and relevant field experiece can earn over $250,000 per year with salary plus incentives.

The hourly salary range for data scientist contract positions is $30-$85, dependent upon skills and project requirements.



Data Scientist Education Requirements

The education requirements for data scientists are among the steepest of all IT occupations. Approximately 40% of data scientist positions require an advanced degree, such as a Master's, MBA or PhD. Others companies will accept data scientists with undergraduate diplomas in an analytical concentration, such as Computer Science, Math & Statistics, Management Information Systems, Economics, Engineering and Hard Sciences.

Schools also offer career-focused courses, degrees and certificates in analytical disciplines like database management, predictive analytics, business intelligence, big data analysis and data mining, all of which provide a solid base for a data scientist career. Targeted training programs like these also present a great way for current business and IT professionals to learn the skills required to break into this red-hot field.

Research and compare data science training programs and business intelligence degrees online.


Data Scientist Training Programs

Research and compare accredited college degrees, professional certificates and self-paced online courses matching data scientist education requirements.

Admissions advisors can provide more info about data scientist programs & curriculum, admissions and start dates, career placement, tuition costs and personalized financial aid options.
Got targeted learning goals? Many schools offer individual courses from accredited degree programs.
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Data Scientist Certifications

Database management and BI certifications for the leading database systems, e.g., Oracle & SQL Server, are consistently in demand at companies and public sector organizations that use these DBMSes for data management and analysis.

When it comes to "big data," most certifications come directly from the leading analytics software providers, i.e., EMC, SAS and IBM. While well-designed, the obvious limitation of vendor-sponsored credentials is their tendency to be specific to the certifying company's product line. One stand-out in this area is EMC's Data Science Proven Professional certification, as it covers a range of vendor-neutral big data tools, techniques & best practices.

Here are some of today's most marketable data scientist certifications:

New data scientist certifications will be added here as they launch.


Data Scientist Jobs

Your specialized data scientist education and experience may qualify you for a variety of job roles including:

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Data Scientist Job Outlook

Data scientists will enjoy one of the brightest job outlooks of all IT occupations through 2020. Data science and analytics is home to a substantial – and fast-growing – talent gap in the IT workforce, meaning there are more job openings than qualified data scientists to fill them.

63% of IT executives polled in a 2011 study by leading IT service firm EMC, suggests the demand for data scientists will significantly outpace (31%) or outpace (32%) the supply of talent through 2018. Another comprehensive report from the McKinsey Global Institute forecasts a shortage of up to 190,000 data scientists in the U.S. by 2018.

Data- and big-data scientists are sought-after at today’s top high-tech and social media giants. Search your favorite job boards for “data analyst” or “big data” and you’re likely to see companies such as Facebook, LinkedIn, Groupon, Spotify & Amazon seeking fresh talent. These businesses amass incredible amounts of raw data, and understand well the game-changing advantages that await the first-movers to capitalize on the big data explosion.

Health care is another hot area for data scientist hiring; with its widespread and ongoing migration to electronic patient records, the medical industry is building data sets to rival the largest enterprises. Other industries aggressively hiring big data scientists include government agencies, social networking hubs, big-box retailers and the U.S. military.

Data is the new oil. Unfortunately, the technology has evolved faster than the workforce skills to make sense of it, and organizations across sectors must adapt to this new reality or perish.

-Andreas Weigend, Head of Stanford’s Social Data Lab and former Chief Scientist at Amazon

Sources: EMC Data Scientist Study, 2011 | McKinsey Global Institute Big Data Report, 2011


Related Career Paths


Subject Matter Expert Contributor

IT Subject Matter ExpertDaniel Greenspan is an IT education specialist and the founder of ITCareerFinder. Working closely with IT professionals, world-class trainers and tech executives since 2005 has given him a unique perspective into the information technology job market and the skills and credentials IT pros need to succeed.