Data Science & Analytics
Data scientists, analysts and quantitative analysts have strong quantitative backgrounds, and advanced degrees are often an asset (if not a requirement) in this space. People in these roles employ a variety of programming languages, statistical tools, and specialized skills to work with and understand large data sets to develop data-informed solutions. Essentially, professionals in this space combine programming with statistics to develop solutions for business problems.
When exploring these job functions, consider:
- what would you like to do with data;
- what type of data would you like to work with;
- and in what field you would like to work?
Be aware that job titles and functions vary across fields and organizations. Here are some preliminary definitions:
- data scientists work with structured and unstructured data. Using algorithms, machine learning, and predictive models, they design and construct novel processes for modeling and production to facilitate strategic decision making.
- data analysts use the data primarily for problem solving – applying their technical toolbelts to find patterns, derive insight, and provide strategic answers to specific questions.
- quantitative analysts, or quants, work in financial spaces – brokerage firms, banks, insurance, investment companies, etc. These analysts conduct analyses to make informed decisions about investments.
Skills to develop for success in this field
The depth of expertise in the below areas required for a role will depend on the level of position candidates are targeting and required foundation for any given opportunity. When applying for different roles, pay close attention to the detailed qualifications and skills outlined in postings or conversations.
Typically, data scientists and analysts need to be able to demonstrate experience in the following areas:
- analytics languages (i.e. Python, R)
- strong statistical and probability theory foundation (i.e. hypothesis testing, statistical significance, linear/logistic regression, Bayesian statistics, Monte Carlo simulations)
- Communication & Collaboration
- experience and comfort with desired tools to help communicate the results of analysis (i.e. PowerBI, Flare, Tableau)
- a track record of effective collaboration and communication with different stakeholders (experts, non-experts, colleagues, external collaborators, etc).
- Data Management
- experience in distributed computing (i.e. Hadoop, Spark)
- experience working with APIs
- a strong foundation in SQL
- Machine Learning/AI
- ML Software tools (i.e. tensorflow, scikit-learn)
Online resources specific to the industry
- Firsthand* is a comprehensive resource for information on what it is like to work within an industry, company or profession. *Note: Registration using Northwestern email address is required for access.
Northwestern Resources and Support
- Integrated Data-Driven Discovery in Earth and Astrophysical Sciences (IDEAS)
IDEAS is a multi-faceted program designed for masters and PhD students in a variety of departments; students can participate at a range of levels. At its core, the program offers a range of coursework in data science. As part of the program, students can also participate in summer school activities focused on data visualizations and computer programming, engage in science communication workshops, participate in the development of a citizen science project related to their research focus, and earn an internship opportunity. More details on the programs are available on our Traineeship page. Students who wish to take only the core coursework will be able to receive a certificate granted by The Graduate School at Northwestern University.
- TGS Integrated Data Science Certificate
Northwestern’s Graduate School offers certificates to help connect doctoral students across various departments and programs. Earning a certificate not only formally recognizes a student’s focus on and achievement in a particular topic area, but helps form a cohort of students and faculty interested in particular interdisciplinary areas. Certificates typically require five course for completion; the certificate will appear on your transcript.
- Northwestern Institute on Complex Systems (NICO)
The Northwestern Institute on Complex Systems was founded in 2004 with the goals of uncovering fundamental principles governing complex systems in science, technology, and human behavior and applying these principles to solve societally relevant problems through the analysis, design, and control of complex systems.
- Graduate students and undergraduate students interested in conducting research and being matched with faculty should enter information on their programming and data science skills, research interests, and time availability here.
Job postings and other career informational sites relevant to the field
Recommendations for internship listings from Vault:
- American Statistical Association
- American Mathematical Society
- Association for Computing Machinery
- IEEE Computer Society
Recommendations for full-time roles from Vault:
Key information or knowledge for this field
Employers are looking for a combination of essential and technical skills and knowledge. They want candidates who can demonstrate the following:
- an ability to communicate effectively across stakeholders with varying areas of expertise – verbally, in writing, and through technical tools
- successful partnerships and collaborations with teams in various settings
- an understanding of (and interest in) the domain and sector to which they’re applying
- evidence of leadership (can be formal or informal) and initiative
- interest in continual learning and growth in an ever evolving space
You can communicate sought-after skills across:
- application documents
- Github profiles to showcase work
- the interview process
If your work doesn’t inherently involve some of the more specialized technical skills, seek out opportunities to develop and demonstrate experience through:
- coursework (institutional and MOOC)
- data science hackathons and competitions
- side projects/contract work
Relevant student groups and professional organizations
Northwestern Graduate Student Organizations:
- Biomedical Informatics and Data Science: The BIDS Student Group was started to bring together graduate students from both the Evanston and Chicago campuses whose research topics and interests lie anywhere within the intersection of healthcare, biology, data science, informatics, statistics and machine learning.
- Academics for Careers in Data Science (ACiDS) is a graduate student group at Northwestern University focused on better preparing for a career in Data Science through:
- Building a portfolio on Github
- Bi-weekly meetings including:
- Coding competency, coding challenges (for interview practice)
- Hack ‘Brunch’ (coffee always served)
- Guest lectures
- No coding experience required
External Professional Organizations:
- American Mathematical Society
A professional society since 1888, we advance research and connect the diverse global mathematical community through publications, meetings and conferences, MathSciNet, professional services, advocacy, and awareness programs.
- American Statistical Society
The American Statistical Association is the world’s largest community of statisticians, the “Big Tent for Statistics.” It is the second-oldest, continuously operating professional association in the country. Since it was founded in Boston in 1839, the ASA has supported excellence in the development, application, and dissemination of statistical science through meetings, publications, membership services, education, accreditation, and advocacy.
- Association for Computing Machinery
The ACM Special Interest Group on Management of Data is concerned with the principles, techniques and applications of database management systems and data management technology. Our members include software developers, academic and industrial researchers, practitioners, users, and students. SIGMOD sponsors the annual SIGMOD/PODS conference, one of the most important and selective in the field.
- DAMA International
DAMA International is a not-for-profit, vendor-independent, global association of technical and business professionals dedicated to advancing the concepts and practices of information and data management.
- Data Science Association (DSA)
The Data Science Association is a non-profit professional association of data scientists that serves our members, improving the data science profession, eliminating bias and enhancing diversity, and advancing ethical data science throughout the world. The DSA is committed to supporting the data science profession with practical resources for data professionals while improving the practice of data science, accrediting schools, and establishing model ethical codes. Membership is open to data scientists, scientists, students, academics, and others interested in science and the data science profession.
- IEEE Computer Society
The IEEE Computer Society is the premier source for information, inspiration, and collaboration in computer science and engineering. Connecting members worldwide, the Computer Society empowers the people who advance technology by delivering tools for individuals at all stages of their professional careers. Our trusted resources include international conferences, peer-reviewed publications, a robust digital library, globally recognized standards, and continuous learning opportunities.
With over 12,500 members from around the globe, INFORMS is the leading international association for professionals in operations research and analytics. INFORMS promotes best practices and advances in operations research, management science, and analytics to improve operational processes, decision-making, and outcomes through an array of highly-cited publications, conferences, competitions, networking communities, and professional development services.