What Can I Do With This Major

Data Science

Data science is an interdisciplinary field that uses various techniques, algorithms, processes, and systems to extract knowledge and insights from structured and unstructured data. It combines expertise from several domains including statistics, computer science, information theory, and domain-specific knowledge.

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Technological & Software Development

Common Career Paths

  • Data analysis
  • Machine learning engineering
  • Data engineering
  • Software engineering
  • Consulting

Employers

  • For-profit and nonprofit organizations
  • Product and service organizations
  • Manufacturers
  • Financial companies
  • Insurance companies
  • Print and electronic media outlets
  • Software and technology companies
  • Internet companies
  • Consulting firms

Strategies

  • Seek programming experience through volunteer positions, internships and co-ops.
  • Develop attention to detail, logical thinking and communication skills.
  • Exhibit patience and creativity for designing programs.
  • Learn to work effectively independently on teams and with end-users while maintaining deadlines.
  • Supplement degree with courses in business, science or engineering.
  • Maintain current knowledge of programming languages; vendor and professional certifications may increase job prospects.
  • Consider earning the Certified Computing Professional designation by completing a series of exams and experiential requirements.
  • Earn a master’s degree for upper level positions.

Finance & Banking

Common Career Paths

  • Data analysis
  • Quantitative analysis
  • Risk analysis
  • Business intelligence analysis
  • Credit analysis
  • Financial data analysis
  • Algorithmic trading
  • High-frequency trading
  • Financial analytics consulting
  • Trading systems development

Employers

  • Banks
  • Large financial firms
  • Software and technology companies
  • Consulting firms

Strategies

  • Seek broad exposure to business principles while honing statistics and quantitative skills.
  • Gain relevant experience through an internship in an industry of interest.
  • Develop excellent information technology, database management, and programming skills.
  • Learn to use relevant software or tools such as Apache Hadoop, SQL, R, Python, and Tableau.
  • Earn industry certifications (e.g., SAS and Google).
  • Learn to work effectively on interdisciplinary teams and how to communicate data intensive information to colleagues.
  • Develop strong analytical skills and a logical approach to problem solving.
  • Get involved in campus organizations and seek leadership roles.
  • Conduct informational interviews with professionals to learn about various industries or functional areas because data science professionals can fit into a wide array of positions.
  • Consider earning a master’s degree to qualify for advanced opportunities.
  • Stay abreast of industry developments through professional societies and websites dedicated to business analytics, data science, data mining, information technology, or other relevant topics.

Healthcare

Common Career Paths

  • Data analysis
  • Biostatistics
  • Clinical data science
  • Health informatics
  • Bioinformatics
  • Health data analysis
  • Healthcare data engineering
  • Health artificial intelligence
  • Healthcare analytics consulting
  • Quality improvement analysis
  • Digital health
  • Outcomes analysis

Employers

  • For-profit and nonprofit organizations
  • Large healthcare corporations
  • Local, state, and federal government
  • Educational institutions
  • Hospitals
  • Consulting firms

Strategies

  • Develop strong analytical skills and a logical approach to problem solving. Skills in budgeting and cost management are also important.
  • Gain related experience through internships or summer and part-time jobs.
  • Take courses in public health, healthcare, and policy.
  • Learn to manage multiple situations and problems.
  • Be able to communicate effectively with different types of people in various functional areas.
  • Earn an MBA or degree in public health to reach the highest levels of operations management.

Marketing

Common Career Paths

  • Data analysis
  • Recommendation systems engineering
  • Digital marketing analysis
  • Business development analysis
  • Customer insights & brand strategy analysis
  • E-Commerce marketing analysis
  • Marketing insights analysis
  • Market research analysis
  • Marketing data analysis
  • Marketing operations analysis
  • Marketing performance analysis
  • Product research analysis

Employers

  • For-profit and nonprofit organizations
  • Large corporations
  • Marketing research firms
  • Public institutions concerning health, education, and transportation
  • Management consulting firms
  • Advertising agencies
  • Manufacturers
  • Retailers
  • Trade and industry associations
  • Government agencies
  • Nonprofit organizations

Strategies

  • Build a solid background in statistics, mathematics, and behavioral science. Strong analytical and problem solving skills and attention to detail are critical.
  • Learn how to use databases and other marketing and statistical analysis software programs.
  • Get involved with a professor’s research project or pursue an independent study to learn about the research process.
  • Gain experience with data entry and interviewing through part-time jobs or internships.
  • Plan to obtain an advanced degree in business or statistics to qualify for more positions.
  • Graduates with bachelor’s degrees may qualify for entry-level positions such as junior or associate analysts.
  • Work experience in sales and other areas of marketing may prove beneficial.
  • Consider earning the Professional Researcher Certification (PRC) by the Marketing Research Association.
  • Learn to effectively translate and communicate quantitative data in presentations to clients.

Government & Public Policy

Common Career Paths

  • Data analysis
  • Policy analysis
  • Urban planning
  • Consulting

Employers

  • For-profit and nonprofit organizations
  • Government agencies
  • State, local, and federal government
  • Print and electronic media outlets
  • Software and technology companies
  • Consulting firms

Strategies

  • Seek broad exposure to systems of government principles while honing statistics and quantitative skills.
  • Gain relevant experience through an internship in government or public policy.
  • Develop excellent information technology, database management, and programming skills.
  • Learn to use relevant software or tools such as Apache Hadoop, SQL, R, Python, and Tableau.
  • Earn industry certifications (e.g., SAS and Google).
  • Learn to work effectively on interdisciplinary teams and how to communicate data intensive information to colleagues.
  • Develop strong analytical skills and a logical approach to problem solving.
  • Get involved in campus organizations and seek leadership roles.
  • Conduct informational interviews with professionals to learn about various industries or functional areas because data science professionals can fit into a wide array of positions.
  • Consider earning a master’s degree to qualify for advanced opportunities.
  • Stay abreast of industry developments through professional societies and websites dedicated to business analytics, data science, data mining, information technology, or other relevant topics.

Manufacturing & Logistics

Common Career Paths

  • Data analysis
  • Operations analysis
  • Supply chain analysis
  • Logistics analysis
  • Supply chain optimization

Employers

  • For-profit and nonprofit organizations
  • Product and service organizations
  • Manufacturers
  • Financial companies
  • Insurance companies
  • Print and electronic media outlets
  • Software and technology companies
  • Internet companies
  • Consulting firms

Strategies

  • Develop analytics skills for data analysis and processing.
  • Strong communication skills are critical.
  • Develop the ability to take complicated issues/processes and explain them to people without a background in that area.
  • Hone research skills and the ability to learn quickly and retain information well.
  • Exhibit a willingness to learn and research in-depth information about clients’ businesses.
  • Plan to travel and work non-traditional hours.
  • Expect to work closely with senior consultants and partners

Getting Started and Advancing in Major

  • Consider a dual major to help shape toward a particular career, since data science intersects with a number of other fields
    • Examples: Biology for a career in bioinformatics; Political science/criminal justice for career in security and information policy; Fine arts for a career in animation; or, Business for some types of IT careers.
  • Develop strong interpersonal, communication and teamwork skills. Patience and perseverance are essential for data science professionals.
  • Complete informational interviews with current data science professionals to help establish career goals.
  • Obtain an internship, co-op or part-time job in a relevant area to increase employability. Related experience is essential to employers hiring data science majors.
  • Obtain vendor-specific or networking certifications to gain a competitive edge for some positions.
  • Obtain an area of specialization through a master’s degree or by doing advanced coursework.
  • Prepare to learn new information on a regular basis through online discussions, classes, conferences, periodicals, and update your skills accordingly.
  • Note that a major in data science can lead to being a designer, creator, and inventor of new technology. Example areas include artificial intelligence, machine learning, virtual reality, or robotics.

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Related Resources

Occupational Outlook

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