Data Science

Data Science involves the use of computer science-based tools to compile, define, and interrogate data sets. Data Scientists, Analysts, and Software Designers are in ever-increasing demand due to the rise of Big Data- data sets of more than 1 TB- in the physical and medical sciences, as well as other fields such as finance and insurance. A career in this field may combine programming, analytics, advanced statistics, data communication, and/or software development. A subfield of Data Science, Bioinformatics and Computational Biology, specifically applies computational research and analysis methods to biological data, notably in the “-omics” (genomics, proteomics, etc.) and evolutionary biology.

Examples of institutions where you could work in this field:

Research Computing Centers
Biotech/Tech Start-Ups
Actuarial Consulting Firms

Examples of job titles that you might find at those institutions:

Data Analyst, Data Scientist, Data Manager, Database Administrator, Bioinformatician, Software Engineer

Professional societies that are relevant to this career category:

International Society for Computational Biology, The Bioinformatics Organization, International Society for Clinical Biostatistics

Alumni Working in Data Science

Ryan Mastro

PhD Neurobiology 2006
Vice President, Employer & Individual Data & Analytics, United Healthcare

What did you do as a trainee to prepare for your current career?
Courses with a bent towards math, stats, and quantitative analyses proved invaluable.

What are the typical things your job entails each day?
I lead a team that houses, manipulates, and analyzes large (to very large) data sets for strategic business planning purposes. At this point in my career, my role is more about leading execution of large projects/programs, but I also spend quite a bit of time managing a budget, in individual management and development, socializing recommendations based on our analyses or reports, and taking recommendations to senior and executive leadership on the marriage between effective data stewardship and impactful business and advanced analytics.

What is the most rewarding part of your job?
Using data to drive insights in as objective a manner as possible is exciting. Staying at the cutting edge of data architecture and warehousing strategy and the cutting edge of advanced data analytics (machine learning, neural networks, etc.) is really fascinating. I also love leading a team, helping and watching people develop and grow their professional skills and realize their potential. It also helps to be part of a company whose mission is helping people live and lead healthier lives and using data and analytics to positively impact the way people engage and manage their health and well-being.

Melissa Runfeldt

PhD Computational Neuroscience 2014
Data Scientist, Salesforce Einstein

What did you do as a trainee to prepare for your current career?
In general: learned new skills, stepped outside of my comfort zone, challenged myself technically, and tackled difficult programs. More specifically: learned to program, analyzed lots of data, gained algorithm intuition, and both took and TA’ed applied mathematics classes.

What are the typical things your job entails each day?
About two-thirds of my job is spent programming, building, and modifying automated machine learning applications, and the other one-third is spent communicating and coordinating with other teams and individuals.

What is the most rewarding part of your job?
Working as a part of a diverse and talented team towards shared goals, learning new skills and technologies, and seeing the impact of my work in customers’ success.