Senior Data Scientist (2-Year Temp Position with Potential for Permanent Hire)

Metropolitan Council•390 Robert St. N St. Paul, MN

7d•Hybrid

About The Position

The Metropolitan Council is seeking a Senior Data Scientist for a 2-year temporary position with the potential for permanent hire. This role is part of the Community Development Research department, specifically within the Strategy and Product Design team. This team focuses on creating accessible digital research products by integrating user experience (UX) design principles and product thinking. The Senior Data Scientist will support the department's mission by modernizing the Community Profiles application and developing the Imagine 2050 Outcomes Measurement Program dashboard. These projects will involve data transformations, statistical modeling, and leveraging a new cloud-based analytics platform (Azure Databricks). The position is eligible for a hybrid telework arrangement, with the candidate's permanent residence required to be in Minnesota or Wisconsin.

Requirements

High school diploma/GED with eight (8) years of experience in advanced data analysis and statistical modeling; developing web based interactive applications or similar digital research products for data visualization or modeling; applied data modeling or engineering.
Associate degree with six (6) years of experience in advanced data analysis and statistical modeling; developing web based interactive applications or similar digital research products for data visualization or modeling; applied data modeling or engineering.
Bachelor's degree with four (4) years of experience in advanced data analysis and statistical modeling; developing web based interactive applications or similar digital research products for data visualization or modeling; applied data modeling or engineering.
Master's degree with two (2) years of experience in advanced data analysis and statistical modeling; developing web based interactive applications or similar digital research products for data visualization or modeling; applied data modeling or engineering.
Degree field of study in Mathematics, Applied Data Analytics, Data Science, Computer Science, Social Sciences, or another related quantitative field.

Nice To Haves

Experience working with Twin Cities (Minneapolis-St. Paul) regional datasets.
Proficient programming skills in SQL, R, and/or Python for statistical modeling, data analysis, data visualization, and/or data engineering.
Experience with Tableau, R Shiny, and/or equivalent business intelligence software to build interactive applications.
Experience working in racially, ethnically, and culturally diverse, multicultural, and inclusive environments.
Experience with cloud-based data platforms or warehouses like Azure Databricks (preferred), Apache Spark, Snowflake, or equivalent database management systems.
Experience with geospatial analysis and databases, and/or ESRI GIS software, including ArcGIS Pro, ArcGIS Online (AGOL), and Enterprise Portal.

Responsibilities

Produce data assets for digital research content
Collaborate with research staff to develop conceptual, logical, and physical data models in a new enterprise-wide Azure Databricks open lakehouse environment to support external applications.
Lead data analysis efforts by developing innovative approaches and applying advanced statistical methods across diverse data sources, delivering trustworthy, well-documented data pipelines.
Partner with subject matter experts and data stewards across the division to develop short- and long-term best-fit data ingestion and maintenance strategies for internal data sources that meet product-based data specifications.
Participate in relevant communities of practice; share and learn from staff peers to advance the department’s practices and governance of the division’s lakehouse.
Build and support digital research products
Collaborate with team to scope, design, build, and performance-tune digital research products using Tableau, R and R Shiny, ESRI ArcGIS Online and Enterprise Portal, and other software/tools as required.
Use data visualization best practices to translate complex research concepts and findings into usable and accessible tools for a diverse user base.
Apply user experience and user interface (UX/UI) design principles and findings from user experience research to digital research products to ensure successful outcomes.