20 most popular jobs upon graduation for those majoring in data science, statistics, or applied math

Here’s a clear, practical guide to the 20 most popular jobs for graduates with degrees in Data Science, Statistics, or Applied Mathematics. These majors build analytical muscle, comfort with coding, and a knack for problem-solving. Employers like these grads because they can dig into messy data, find patterns, and explain results in ways that drive decisions. While some jobs sit squarely in tech, others are in finance, healthcare, government, and even sports or retail.

• Data Analyst
  Collecting, cleaning, and visualizing data to support decisions in business, healthcare, government, or nonprofits.
• Business Intelligence Analyst
  Building dashboards, reports, and KPIs to help leadership track performance and spot opportunities.
• Data Scientist (junior level)
  Applying machine learning and statistical models to real-world problems like churn prediction, fraud detection, or personalization.
• Quantitative Analyst (Quant)
  Using mathematical models to price securities, manage risk, or design trading strategies in finance.
• Risk Analyst
  Measuring and reporting financial, operational, or credit risks in banks, insurers, and corporations.
• Actuarial Analyst
  Supporting actuarial teams in insurance or pensions with statistical modeling and forecasting.
• Operations Research Analyst
  Optimizing logistics, supply chains, and resource allocation for efficiency and cost savings.
• Market Research Analyst
  Designing surveys, analyzing consumer data, and presenting insights for marketing and product teams.
• Machine Learning Engineer (entry-level)
  Assisting with building and deploying predictive models; often bridges data science and engineering.
• Data Engineer (junior)
  Designing pipelines, warehouses, and ETL processes to make data accessible to analysts and scientists.
• Product Analyst
  Studying user behavior, running A/B tests, and advising product teams on what features to prioritize.
• Healthcare Data Analyst
  Working with patient records, clinical outcomes, and public health datasets to improve care delivery.
• Sports Analyst
  Using data to evaluate performance, strategy, and recruitment in professional or collegiate sports.
• Economist (applied roles)
  Supporting government agencies, think tanks, or corporations with forecasting and policy modeling.
• Research Scientist Assistant
  Supporting academic, corporate, or government research projects with statistical programming and analysis.
• Fraud Analyst
  Spotting suspicious activity in banking, payments, or e-commerce using data patterns.
• Customer Insights Analyst
  Mining data from loyalty programs, purchase histories, or digital interactions to improve marketing campaigns.
• Logistics / Supply Chain Analyst
  Using math and simulation to optimize delivery routes, warehouse flows, and demand planning.
• Credit Analyst (quantitative track)
  Evaluating creditworthiness and modeling repayment risk for individuals or businesses.
• Policy Analyst (quant focus)
  Working in government or NGOs to evaluate the impact of programs using statistical methods.

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How to Use This List

Data-driven roles are in demand everywhere. The real edge isn’t just being able to run regressions or code in Python—it’s showing you can turn numbers into outcomes. Employers want to see proof: a dashboard that saved time, a model that predicted demand, or an analysis that improved decisions. Whether you join a big company, a government agency, or a startup, the ability to explain data clearly and connect it to action is what will set you apart.