Data Scientist

Universities of Wisconsin•Madison, WI

1d•$70,000 - $110,000•Onsite

About The Position

The Data Science Institute (DSI) is a campus-wide research institute focused on growing the university's research enterprise and expanding its global impact. The DSI team, comprising data scientists, software engineers, and AI engineers, collaborates with faculty, students, and industry partners on diverse research problems. The role involves scoping new collaborations, developing data science pipelines, reviewing statistical analyses, teaching workshops, and mentoring students. DSI is a key partner in the Wisconsin Research, Innovation and Scholarly Excellence (RISE) initiative, which aims to expand research capacity and investment in AI, sustainability, and health. This expansion increases the demand for data scientists to support ambitious research goals.

Requirements

Demonstrated experience with data science and computational workflows, including data wrangling, cleaning, modeling, visualization, and analysis.
Demonstrated programming experience in at least one language commonly used for data science (Python, R, Julia, or comparable).
Demonstrated ability to take a vague research question, sharpen it into something answerable, and deliver results that move the work forward.
Strong written and oral communication, including the ability to explain technical work to non-technical collaborators and to build consensus across disciplinary boundaries.
Ability to work independently and as part of a team, set priorities, exercise good judgment about where to invest effort, and adapt as projects evolve.

Nice To Haves

Experience with AI/ML frameworks such as PyTorch, JAX, TensorFlow, or Keras.
Experience with MLOps tools such as Weights & Biases, MLflow, or Neptune.
Experience with distributed computing systems: cloud (AWS, Azure, GCP), high-performance computing (HPC), or the UW-Madison Center for High Throughput Computing (CHTC).
Experience with containerization (Docker), package and release workflows, and continuous integration / continuous deployment (CI/CD) using tools such as GitHub Actions or GitLab CI.
Experience building stakeholder-facing tools such as dashboards or web portals.
Collaborative Git practice: branches, pull requests, and code review.
Writing and maintaining automated tests for the code you ship (unit-level at minimum).
Managing reproducible computing environments using tools such as venv, conda, uv, or pixi.
Experience working in a research environment and engaging with highly technical researchers across multiple methodological fields, research domains, and computational platforms.
Experience in a consulting or services role: making first contact, working with a researcher to understand the underlying need, breaking a research problem into pieces with clear deliverables, scoping a statement of work, and managing the project through delivery.
Experience contributing to grant proposals or other sponsored-research activities.
Teaching, mentoring, or training experience.
A track record of positive impact on your local working environment.

Responsibilities

Composes and assembles reproducible workflows and reports to clearly articulate patterns to researchers and/or administrators.
Prepares data sets for analysis including cleaning/quality assurance, transformations, restructuring, and integration of multiple data sources.
Documents approaches to address research questions and contributes to the establishment of reproducible research methodologies and analysis workflows.
Independently identifies and implements appropriate data science techniques to find data patterns and answer research questions chosen by the lead researcher including data visualization, statistical analysis, machine learning, and data mining.
Organizes and automates project steps for data preparation and analysis.
Engages in project intake, scopes new collaborations with researchers, and drafts statements of work for incoming engagements.
Contributes to DSI's programmatic activities, including workshops, training, graduate student mentorship, and the institute's internal life.