Data Science: Statistical Modeling

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Bachelor of Science in Data Science: Statistical Modeling Concentration

Top 5 Reasons to Study

Gain the knowledge, skills, and confidence to leverage advanced statistical methods and theory to build rigorous analytical models for complex real-world problems, positioning yourself for careers in statistical research and quantitative analysis.

Learn to design and implement statistical models (including regression, Bayesian methods, time series analysis, multivariate techniques, machine learning, and experimental designs) to discover, validate, and predict patterns in data.

Dive deeply into the foundations of quantitative analysis to understand both how and why statistical methods work, enabling you to select appropriate techniques, assess model validity, interpret results correctly, and develop novel approaches.

Build robust analytical solutions through rigorous statistical modeling by applying mathematical and AI machinery to real-world big data challenges, ensuring predictions and inferences are statistically sound, reproducible, and defensible.

Gain the quantitative depth to solve complex problems with precision and confidence by validating discoveries with statistical rigor, quantifying uncertainty in predictions, and bringing mathematical sophistication to data-driven decision-making.

Core
Skills

Build and apply advanced statistical methods and employ the theoretical machinery of quantitative methods.
Predict trends and identify patterns based on statistical analysis, using large datasets to uncover insights.
Discover patterns in big data by designing models that address real-world challenges.

Sample
Jobs

Statistician
Quantitative Analyst
Risk Anaylst
Operations Research Analyst
Finance Analyst

Successful Career Outcomes

$103,500 Median Annual Salary

35% 10 Year Growth Expected

Top
Employment
Industries

Statistical Research: Designing rigorous analytical models and validating discoveries in every field
Quantitative Analysis in Finance, Insurance, Sports: Applying mathematical machinery to real-world challenges
Data Science Leadership: Leading technical roles requiring strong mathematical foundations
Science and Academia: Ensuring reproducibility and sound inference in scientific fields
General Business: Bringing mathematical sophistication to decision-making across industries

Brag
Points

Study with the best: data science majors at MSU have a median ACT score of 29
Our students have access to Ptolemy, a 64 GPU NVDIA system dedicated to academic use
38% of our Data Science students participate in the Shackouls Honors College

Experiential Learning Opportunities

Capstone Project: You will participate in a two-semester capstone experience in which you will be matched with a geoscience faculty mentor as you pursue a meaningful project.

Athletics Data Science and AI Lab: Our undergraduate students work to centralize, connect, and translate athletic data into actionable insights that support smarter decisions across the entire athlete lifecycle.

Department of Mathematics and Statistics: Our department encourages undergraduate research in applied statistics. You can work with faculty on problems ranging from environmental modeling to financial risk analysis.

Data Science Academic Institute: Our undergraduate researchers work on faculty projects in diverse subject areas.

You'll take five hands-on labs that use real data. This builds career-relevant experiential learning directly into your coursework.