Data scientists analyze organizational data for actionable intelligence.
Data scientists mine and analyze data from various 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 scientists among the most sought-after and lucrative IT careers. Data scientists’ salaries 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 healthcare 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.
a.k.a. Data Architect | Big Data Scientist | BI Analyst | Data Engineer | Information Scientist
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
According to the latest data from the U.S. Bureau of Labor Statistics, the median annual salary for data scientists is $104,000.
Here are the average salaries for data scientists and related positions:
| Data Science Career | Average Salary |
|---|---|
| Junior Data Scientist | $80,000 |
| SAS Data Analyst | $90,000 |
| IBM Data Analyst | $91,000 |
| Business Intelligence Analyst | $100,000 |
| Data Mining Engineer | $121,000 |
| Data Scientist | $122,000 |
| Business Intelligence Architect | $128,000 |
| Senior Business Intelligence Analyst | $129,000 |
| Data Warehouse Architect | $130,000 |
| Data Architect | $149,000 |
| Senior Data Scientist | $177,000 |
These are the top-paying cities and metropolitan areas for data scientists:
| City or Metro Area | Data Scientist Salary |
|---|---|
| San Jose / Sunnyvale / Santa Clara, CA | $233,000 |
| San Francisco / Oakland / Hayward, CA | $152,000 |
| Seattle / Tacoma / Bellevue, WA | $143,000 |
| New York City Tri-State Area, NY-NJ-PA | $136,000 |
| Charlotte / Concord / Gastonia, NC-SC | $129,000 |
The business intelligence and data analytics field has practically unlimited earning potential. Talented data scientists with a solid education and relevant experience can earn over $250,000 per year with a base salary plus incentives.
The hourly wage for data scientist contract positions is $48 to $100+, dependent on skills, experience, and project requirements.
Sources: U.S. Bureau of Labor Statistics | Analysis of Online Job Boards
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. Other companies will accept data scientists with undergraduate diplomas in an analytical concentration, such as computer science, 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, 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 analytics associate degrees and business intelligence degrees online.
Related: What Jobs Can You Get With a Data Science Degree?
Data Scientist Training Programs
Research and compare accredited college degrees, professional certificates, and self-paced online courses matching data scientists' education requirements.
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 systems 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, and best practices.
Here are some the top data scientist certifications:
- Microsoft Certified Solutions Associate (MCSA)
- Microsoft Certified Solutions Expert (MCSE)
- Google Data Analytics Professional Certificate
- IBM Data Science 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)
- 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 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 35% from 2022 to 2032, more than 10X than the 3% average for all occupations. As data continues to become the most valuable asset in the global economy, more data scientists will be needed to mine this massive cache of information for actionable insights.
-Andreas Weigend, Head of Stanford’s Social Data Lab and former Chief Scientist at Amazon
Healthcare 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 corporations. 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
Related Career Paths
- Database Administrator
- Software Engineer
- Web Developer
- Computer Programmer
- Graphic Designer
- Cloud Engineer
- Machine Learning Engineer
