Considering a career in data science? Wondering what exactly that entails? Welcome to your complete guide to professional advancement.
The Definition of a Data Scientist
Data science was developed to handle the flood of big data engulfing the world. A blend of statisticians, computer scientists and creative thinkers, data scientists have the:
- Skills to collect, process and extract value from giant and diverse data sets
- Imagination to understand, visualize and communicate their findings to non-data scientists
- Ability to create data-driven solutions that boost profits, reduce costs and even help save the world
Data scientists work in every industry – from the Defense Department to Internet start-ups to financial institutions – and tackle big data projects on every level.
Getting a Degree in Data Science
The best job of the 21st century is only getting better. A McKinsey report estimates that by 2018, the U.S. could face a shortage of 140,000 to 190,000 data scientists and 1.5 million managers and analysts who understand how to use big data to make decisions. Do you have to invest in a master’s degree? Not necessarily. Plenty of successful data scientists launched their careers with a B.S. and a hefty handful of skills. However, as data problems become more complex, many big companies are demanding advanced degrees. Top employers by industry include:
- Pharmaceuticals
- Computer Software
- Internet
- Research
- IT and Services
- Biotechnology
They’ll pay you good money for your efforts. In 2013, Silicon Valley salaries for entry-level data scientists were in the low six figures ($110,000-$120,000).
Schools Offering Master’s Programs in Data Science
Ready to make the leap? In our annotated list of top schools, you’ll find information on each program’s:
- Location and length
- Full-time, part-time and online options
- Concentrations and majors
- Courses, internships and real-world opportunities
Look for quality. Universities are scrambling to offer new degrees, but there’s no guarantee they’ll be worth the investment. Research the background of the program and professors. Search for solid partnerships with businesses and research institutions. Ask about job placement figures. You deserve a practical qualification.
Data Science Industries
Focusing on a particular industry? We’ve created a reference for past, present and future to help you prepare for what’s ahead. On each industry page, you’ll discover:
- A condensed history of data science within the field
- Current opportunities and developments
- Examples of vendors and big data projects
- Data-related risks and regulations
We don’t discuss many typical day-to-day tasks or job titles primarily because these vary widely among employers. Indeed, the first requirement on many job listings is flexibility.
Data Science Blog
Need more guidance? Grab a cup of coffee and browse our data science blog. We’ve included articles such as:
- Data Scientist Foundations
- Open Source Tools for Big Data Analysis
- New Technologies in Data Science
They’re all designed to provide you with a practical knowledge base to help launch your career.
