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BS/MS Data Science Dual Degree

Take your career prospects to the next level. Develop your analytical skills and prepare for your future with an accelerated dual degree program in data science.

Program Snapshot

Dual Degree

Graduate

4 Years

Salem Campus

A person looking up in a classroom

Our 3+1 BS/MS in Data Science

The dual degree data science program is designed to prepare you to enter a constantly evolving field. By earning both your bachelor’s and master’s degrees in just four years and a summer, you will benefit from the breadth of our undergraduate offerings and the strengths of our graduate courses. Jumpstart your career and enter one of today’s most in-demand fields with our dual degree program. 

Why pursue a dual BS/MS degree in Data Science at Willamette?

  • Flexibility for you. Graduate courses are offered in both Salem and Portland so you can learn in a convenient location. Classes are also held in the evenings so you can work while completing your degree. 
  • Increase your earning potential. With the dual degree program, you will graduate in four years instead of the usual five, giving yourself an extra year of earning power. 
  • Access to unique benefits. Join specific career events for data science through our School of Computing and Information Sciences.

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Alumni Stories

Data science alumni have applied their skills and expertise to a variety of fields such as medicine, business, and environmental science. They’ve accepted positions with major companies and built impressive careers. Find out more about how data science graduates are having an impact using new and evolving technology.

  • Zach Haroian BS/MS ’21

    Advancing Data Science at PitchBook
    Zach Haroian, the first graduate of Willamette University’s 3+1 BS/MS in Data Science program, secured a position as an associate machine learning engineer at PitchBook before even graduating. Haroian is using his skills to build models that analyze text data for financial insights, applying much of what he learned during his dual degree program.

    Zach Haroian

Our Faculty

Our faculty is comprised of experienced professionals actively working in their respective fields. Because of this, they are able to offer students the most up-to-date industry insights. Through one-on-one mentorship, professors provide personalized support and access to professional networks.
  • Meet Dr. Kristen Gore

    Professor Gore brings extensive experience from her tenure at HP Inc., where she led statistical data strategies and quality systems for advanced technology platforms. In addition, she has a passion for STEM outreach, serving as a LEGO robotics volunteer.
    Portrait of Kristen Gore
  • Meet Dr. Calvin Deutschbein

    Professor Deutschbein, an expert in computer security and systems. Their research has gained recognition from industry leaders like Intel and the Semiconductor Research Corporation, as well as at prominent hardware security conferences.
    Photo of Professor Deutschbein
  • Meet Dr. Heather Kitada Smalley

    Professor Kitada Smalley, Willamette’s Albaugh Assistant Professor of Statistics, is an applied statistician with expertise in survey methodology and data visualization using R. Her work has been recognized nationally, and her research explores bias estimation in public opinion surveys, experimental design, and educational rese
    Kitada Smalley headshot

Curriculum

Our data science BS and MS programs cover everything from technical skills to critical thinking. While undergraduate courses create a foundation of knowledge, graduate courses go further in depth, building your proficiency with systems and programs. The curriculum of both programs will help students gain the expertise they need to prepare for an evolving field.

  • DATA 501 Foundations of Data Science with R

    Discover the power of R and Python in our data science dual degree! Dive into the tidyverse ecosystem, master key programming skills, and tackle real-world projects. Communicate your findings and showcase your value at every step.

  • DATA 505 Applied Machine Learning

    Explore machine learning through practical applications like personalized recommendations, image processing, and speech recognition. With lectures, cases, and programming projects, you'll learn to solve real-world problems, run evaluations, and interpret results using existing machine learning libraries.

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