The DATA Science Credential

Combining the “What” with the “Why” & “How”

The Data (Data-Acumen-Theory-Application) Science Credential in Economics helps Economics majors receive in-demand data skills, guided by theory, applied to economics.

We initiated the credential in 2021. We recognized employer demand for skills in data science and, in particular, the advantage of having that skill set along with an understanding of its application to the many economic challenges and questions that firms face every day. Fast forward three years to 2024, and our university now has a School of Data Science and Society (SDSS) that offers a BA and a BS degree in data science, and the College is offering a minor in data science. The economics department has made sure that our courses fulfill some of the requirements of those degrees. We have an Economic Analysis Concentration in the BS degree and several of our courses appear on the elective list for the minor.

We will continue to offer data science-related courses and applications and to bring in speakers from industry for the DATA Science seminar series. Students who complete the sequence of courses and attend four speaker events are encouraged to list the credential on their resumes. While the university does not indicate this type of credential on student transcripts, we have developed common language (see below) that can be used by our majors to signal the accomplishment. Also, given the many ways a student can acquire data science skills, the economics department will no longer recognize recipients of the credential in an end-of-year ceremony, but we can provide you with a certificate of completion at your request.

If you have any questions, please reach out to our Director of Undergraduate Studies.

Completion of the credential requirements allows students to obtain:

Practical and Marketable Skills
Introduction to programming languages (e.g., R/Python) commonly used in applications of data
science, and practical data skills: collecting, scraping, cleaning, merging, processing, and visualizing
data, descriptive analysis, optimization, and supervised/unsupervised statistical learning.

Synergy, Application, and Experience
Gain experience in combining these data skills with foundational knowledge of economics to frame
and solve economic questions using real data from finance, industry, government, health,
environment, among others.

Credential Requirements
The Credential requirements include completion of three courses and attendance at the Credential Speaker events.

• Three Courses*
  • ECON 370: Economic Applications of Data Science
  • ECON 470: Econometrics
  • ECON 573: Big Data and Machine Learning
    • or ECON 571: Advanced Econometrics
    • or ECON 575: Applied Time Series Analyses and Forecasting
• Seminar Series: Attendance at seminars (minimum: 4) of invited speakers from industry to learn about the practice of data science and to provide opportunities for career networking.
  • Speaker Series
    • Spring 2024
      • Michael Danke, Academy Sports
      • Erin Seaverson and Dan Beutler, WebMD
      • George Korenko, Edgeworth Economics
    • Fall 2023
      • Krystal Lo, J.P. Morgan
      • Zhou Zhang, Cambly
    • Spring 2023
      • Kang Jian, Teladoc Health
      • Ju Hyun Kim, Blue Cross Blue Shield
      • Josh Patterson, Voltron Data
    • Fall 2022
      • Laura Perkins & Josh O’Donnell, AlixPartners
      • Gyasi Dapaa, Indeed
      • Sean Olson, Booz Allen Hamilton
    • Spring 2022
      • Philip Nutsugah & Christian Welin, Cox Communications
      • Wade Kimbrough, Volatility Protocol
    • Fall 2021
      • Nickolai Riabov, Airbnb
      • Yanik Lacroix Torrent & James Cardiff, West Jet
      • Stella McMullen, Zillow
• Data Science Competitions: Optional participation with a team of students in competitive challenges to explore and analyze a provided data set to answer important economic questions.

The credential is officially conferred to a student at the end of the semester in which all requirements are met.

On Résumé
We hope you will list this achievement on your resumé. For uniformity, the Economics Department would like all students to reference the DATA Science Credential in the same way on your resumés (since there is no formal university distinction for such credentials on the transcript). We suggest the following:

• Put the following citation under the “Education” section of resumé, indicating (expected) date of completion of requirements: 
  • DATA Science Credential in Economics (month year)

• For elaboration when necessary, use: 
  • The DATA Science Credential (Data|Acumen|Theory|Application) is implemented by the Economics Department at UNC Chapel Hill to provide experience in combining data skills (i.e., collecting, scraping, cleaning, merging, processing, and visualizing data, descriptive and econometric analysis, optimization, and supervised/unsupervised statistical learning) with foundational knowledge of economics to frame and solve economic questions using real data.