Earn a Bachelor's Degree in Data Science

A bachelor of science in data science equips students with the analytical, computational, and statistical skills needed to extract insight from complex data and solve real-world problems. This interdisciplinary program integrates core principles from computer science, mathematics, and statistics, preparing graduates to thrive in a data-driven economy across a wide range of industries.

Students gain a strong STEM foundation while developing hands-on experience with modern data science tools and methodologies. The program prepares graduates for high-impact careers in industry, government, and research, as well as for advanced study in data science and related fields.

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Degree Information

Data science sits at the intersection of multiple disciplines. At Missouri S&T, students develop technical expertise supported by theoretical foundations, enabling them to adapt as tools and technologies evolve.

Students build competencies in:

  • Programming and algorithmic thinking
  • Statistical modeling and data analysis
  • Data management and databases
  • Machine learning and artificial intelligence
  • Ethical and responsible data use
  • Communication of data-driven insights

The curriculum emphasizes both foundational understanding and practical application, preparing students to address challenges in fields such as healthcare, finance, manufacturing, energy, transportation and technology.

The bachelor of science in data science consists of 120 credit hours and features two emphasis areas, allowing students to adjust the degree to their interests and career goals.

All students complete:

  • 48 credit hours of core coursework in mathematics, statistics and computer science
  • 21 credit hours in a chosen emphasis area
  • General education requirements and free electives to support interdisciplinary exploration

Mathematics and Statistics Track

This track emphasizes probability modeling, statistical theory, and mathematical foundations that support advanced data analysis and machine learning. Students gain the depth needed to understand not just how to apply data science methods, but why they work.

 Computer Science Track

This track focuses on computational methods, artificial intelligence and scalable data systems. Students develop strong programming and algorithmic skills for building data-driven solutions in complex computing environments.

The data science curriculum provides a common interdisciplinary core while allowing specialization through emphasis areas and electives.

Core coursework includes:

  • Calculus, linear algebra and probability
  • Statistical data analysis and regression
  • Programming and data structures
  • Databases, algorithms and introductory data science

Upper-level coursework introduces topics such as machine learning, artificial intelligence, causal data science, statistical learning, data mining and domain-specific applications.

Experiential learning is a hallmark of Missouri S&T. All data science students complete an experiential learning requirement, applying classroom knowledge to real-world problems.

Experiential opportunities include:

  • Undergraduate research
  • Internships and co-ops
  • Industry-sponsored projects
  • Student design teams and competitions
  • Leadership, service learning and mentoring experiences

These experiences ensure graduates are career-ready and confident in applying data science skills in professional settings.

Your Career in Data Science

S&T’s bachelor’s degree in data science opens doors to rapidly growing, high-impact career paths. Graduates are prepared to work across industries that rely on data-driven decision-making and predictive analytics.

image of a briefcase icon encircled by a dark green background and a lime green outer ring Career Pathways

Graduates are also well prepared to pursue graduate study in data science, computer science, mathematics, statistics, or related disciplines, as well as careers such as:

  • Data scientist
  • Data analyst
  • Machine learning engineer
  • Business intelligence analyst
  • Statistical analyst
  • Software and data engineer
  • Operations and systems analyst

Research in Data Science

Research in data science at Missouri S&T spans multiple departments and application areas, supported by faculty expertise in mathematics, statistics and computer science.

Specialized Areas of Research

Undergraduate research opportunities allow students to work alongside faculty on cutting-edge projects and contribute to real-world discoveries.

  • Machine learning and artificial intelligence
  • Causal and statistical data science
  • Data mining and large-scale data systems
  • Computational modeling and simulation
  • Data visualization and decision support
  • Ethical and responsible data use

Program Admissions Overview

Ideal Candidates for Admission

The data science degree is designed for students who are curious, analytical and motivated to solve real-world problems using data.

Ideal candidates:

  • Have strong interests in mathematics, statistics, computing or analytics
  • Enjoy problem solving, logical thinking and working with data
  • Are interested in applying technical skills to fields such as technology, healthcare, business, energy, manufacturing or research
  • Seek a rigorous STEM degree with strong career outcomes and flexibility

Students who are undecided between mathematics, statistics and computer science — but are excited by how these disciplines work together — are particularly well-suited for this program.

Applicants must meet standard Missouri S&T undergraduate admission requirements. 

Recommended preparation includes:

  • Four units of mathematics at the Algebra I level or higher
  • Coursework in calculus, statistics, or programming is beneficial but not required
  • Curiosity and willingness to engage in quantitative and computational thinking 

Students will begin building programming, statistical and analytical skills early in the curriculum, with support structures in place to ensure success.
  • Deep STEM integration across mathematics, statistics and computer science
  • Two emphasis areas that allow meaningful specialization
  • Strong preparation for both industry careers and graduate study
  • Built-in experiential learning opportunities
  • Instruction by faculty actively engaged in data science research and education

Graduates leave Missouri S&T prepared not only to use today’s data science tools, but to adapt, innovate, and lead as the field continues to evolve.

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