Data Scientist II or III

University of Wisconsin Madison•Madison, WI

11d•Hybrid

About The Position

The University of Wisconsin Population Health Institute (UWPHI) accelerates capacity to create equitable conditions for everyone to be healthy by advancing knowledge, practice, policy, and systems change across sectors. UWPHI seeks a Data Scientist to help develop tools and resources that focus on the drivers of health and health equity across communities. This role combines rigorous statistical analysis with modern data science practices, including use of GitHub for version control, collaboration, and reproducible analyses. The successful candidate will work with large, complex datasets to generate actionable insights on population health for public health and health care audiences. Using tools such as R, Python and SQL, the Data Scientist will help design, document, and share analytical workflows and interactive dashboards that inform local decision-making. Ideal candidates are detail-oriented, collaborative, and committed to high-quality, open, and policy-relevant research. This position may require some work to be performed in-person, onsite, at a designated campus work location. Some work may be performed remotely, at an offsite, non-campus work location. Applicants for this position will be considered for the following titles Data Scientist II or Data Scientist III. The title is determined by the experience and qualifications of the finalist. University sponsorship is not available for this position, including transfers of sponsorship and TN visas. The selected applicant will be responsible for ensuring their continuous eligibility to work in the United States (i.e. a citizen or national of the United States, a lawful permanent resident, a foreign national authorized to work in the United States without the need of an employer sponsorship) on or before the effective date of appointment. This position is an ongoing position that will require continuous work eligibility. If you are selected for this position, you must provide proof of work authorization and eligibility to work.

Requirements

At least five years of relevant experience in health-related applied research, statistics, and analytics.
Advanced proficiency with statistical software and programming languages, specifically Python and R.
Experience using and managing workflows in open-source platforms like GitHub, for version control, code management and collaboration.
Proficiency in interactive web dashboards and applications built with tools such as Shiny, Quarto, Streamlit or Dash for visualizing and disseminating data.
Experience manipulating and analyzing a variety of datasets including, national mortality, community health, health indicators and outcomes, including non-traditional data sources such as (grassroots reporting/social media mining).
Experience developing analytic approaches to support continued improvement of data management, analysis, visualization and presentation, including the development of data quality frameworks.
Ability to identify data needs, and experience curating data from a variety of sources, assessing limitations and data quality, to manage, aggregate, and document for a particular use.
Exceptional written and verbal communication skills
Ability to independently problem solve and adapt
Ability to work in a hybrid work environment with various stakeholders, both internally and externally

Nice To Haves

Proficiency in SQL for querying, transforming and optimizing large relational databases.
Strong understanding of cloud data ecosystems, including cloud storage, data warehousing, data pipelines, and big data processing frameworks.
Experience with AWS, Azure, or GCP and tools like Snowflake, Spark, and Databricks is highly desirable.
Familiarity with developing and sustaining processes for efficient data extraction, including for example building an Application Programing Interface (API) and automated ETL pipelines.
Experience or interest in integrating Generative AI/LLMs to enhance data analysis and to build conversational tools (e.g., chatbots) that help public users easily explore web-based data products.

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