Data Scientist Career Path & Training

data scientist training
Data 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 sought-after 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 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 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, 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 | Big Data Scientist | BI Analyst | Data Mining Engineer | Information Scientist

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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

The mean annual salary for data scientists in the US is $104,000, according to the latest data from US Bureau of Labor Statistics.

Data Scientist Salary $104,000

 

Salaries for data scientists and related positions:

  • 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 Scientist: $104,000
  • 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
  • Senior Data Scientist: $130,000
  • Senior Big Data Analyst: $138,000

Top paying US cities and metropolitan areas for data scientists:

  1. San Francisco / Oakland, CA: $149,000
  2. San Jose, California: $146,000
  3. New York City Metro Area: $129,000
  4. Seattle, Washington: $121,000
  5. Los Angeles, California: $118,000

The business intelligence & analytics field has practically unlimited earning potential. Talented data scientists with a solid education and relevant field experience 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.

Sources: US Bureau of Labor Statistics | Indeed.com

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.

Bachelor's in Computer Science - Data Analysis

  • Gain the Skills and Credentials to Pursue Sought-After Careers in Data Management
  • Create and Manage Structured Databases
  • Analyze Data to Meet Organizational Goals
  • Advanced Statistics for STEM Disciplines
  • Use Emerging Tech in Cloud Computing, Artificial Intelligence (AI) and Machine Learning (ML) to Analyze Big Data
 

Master of Science in IT - Analytics

  • Use analytics, statistics & forecasting to drive smarter business decisions
  • Identify relevant data and sources to solve complex business problems
  • Address global, ethical, legal & cultural factors in data analytics
  • Create effective data visualizations and stakeholder presentations
  • Must have a bachelor's degree to apply. GRE / GMAT not required.
 

Master's in Technology Management

  • Prepare to Lead IT Personnel and Wield Emerging Technologies to Achieve Business Goals
  • Choose from courses like:
    • Business Intelligence and Data Analytics
    • Cyber Security Threats & Vulnerabilities
    • Managing Diverse Organizations in a Flat World
    • Cloud Computing and Virtualization
    • Computer Systems Analysis
    • Cryptography & Network Security
  • Must have a bachelor's degree to apply. GRE / GMAT not required
 

Google Data Analytics Pro Certificate

  • Includes Certification Preparation for:
    • Google Data Analytics Professional
  • Learn to use Popular Data Analytics Tools inc. Tableau, SQL, R Programming, Spreadsheets & Slideshows
  • Clean, Organize and Analyze Complex Data Sets
  • Data Visualization & Stakeholder Presentation
  • Constructive Questioning and Structured Thinking
 
Search IT courses and degree programs by job role, technology platform & major.

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:

  • Microsoft Certified Solutions Associate (MCSA)
  • Microsoft Certified Solutions Expert (MCSE)
  • Google Data Analytics Professional Certificate
  • Data Science EMC Proven Professional [EMC] (EMC product knowledge + vendor-neutral big data skills)
  • Certified Health Data Analyst [AHIMA] (specific to health care industry)
  • IBM Cognos Business Intelligence certifications [IBM] (specific to IBM analytics products)
  • Apache Hadoop certifications [Cloudera] (specific to the Hadoop open-source analytics platform)
  • SAS Certified Predictive Modeler [SAS] (specific to SAS analytics products)
  • SAS Certified Statistical Business Analyst [SAS] (specific to SAS analytics products)
  • SAS Certified BI Content Developer [SAS] (specific to SAS analytics products)

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:

  • Data scientist jobs link-icon
  • Data analyst jobs link-icon
  • Data architect jobs link-icon
  • Big data jobs link-icon
  • Data mining engineer jobs link-icon
  • Data warehousing jobs link-icon
  • Business intelligence analyst jobs link-icon
  • Business intelligence developer jobs link-icon
  • SAP analyst jobs link-icon

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Data Scientist Job Outlook

Data scientists will enjoy one of the brightest job outlooks over the next decade. The data science job market is expected to grow by 22% from 2020 to 2030, much faster than the 8% average for all occupations over the same period. As social media and high-tech organizations proliferate, and data continues to become the most valuable asset in the global marketplace, more data scientists will be needed to mine this massive cache of information for actionable intelligence.

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

Health care is a notable hot area for data scientist hiring; with its rapid migration to electronic medical 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, retailers, and the U.S. military.

Source: U.S. Bureau of Labor Statistics' Occupational Outlook Handbook


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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.