Data Scientist

Polco; Madison (WI); Hybrid; USD 110,000 - 150,000; Full time

Benefits offered by this job

Hybrid work environment

Flexible work hours

Competitive benefits package

Job summary

Polco is hiring a Data Scientist to synthesize advanced insights for ~400 premier US local governments across 50 states, impacting over 36 million Americans. The role spans descriptive, predictive, and causal analytics, using Python, SQL, and Snowflake.

Preferred candidates are in the Madison, WI area with a hybrid schedule, but remote US candidates will be considered. You'll mentor stakeholders, build scalable data workflows, and collaborate with Engineering, Marketing, and Sales to turn data

Qualifications

• Bachelor's degree or equivalent in a quantitative field; graduate degree helpful but not required.
• 2+ years of applied data science or quantitative analysis experience.
• Proficiency in Python and SQL (required).
• Working knowledge of R or willingness to learn it.
• Strong statistics foundation and interest in causal inference.
• Experience building with agentic AI tools (Claude, Codex).
• Strong written and verbal communication skills.
• Ability to work in ambiguity with startup pace.

Responsibilities

• Maintain recurring data processes for GPAL and analytics databases.
• Build and improve statistical and predictive models using GPAL data.
• Lead advanced client analytics projects and communicate results to stakeholders.
• Collaborate with Engineering to automate data workflows and dashboards.
• Work with Marketing, Sales, CS, and Survey Research on internal analytics.
• Document work for reproducibility and contribute to internal data apps.

Skills

Python

SQL

Statistics

Causal inference

Communication

Applied data science

Project portfolio

Education

Bachelor's degree in quantitative field

Graduate degree helpful

Tools

Snowflake

Claude

Codex

Job description

Polco is hiring a Data Scientist! Polco runs some of the most important local government performance databases in the country, including GPAL, which is a 'Bloomberg Terminal of local government performance.' As a Data Scientist at Polco, you'll help synthesize advanced insights for our roughly 400 premier US local governments across 50 states. With an average population of over 90,000, you'll be positively impacting more than 36 million Americans.

This role spans descriptive analytics (characterizing community trends and benchmarks), predictive analytics (cloud-based machine learning models that show communities where their key metrics are headed), and causal analytics (contributing to the causal econometric work Polco is known for, with mentorship from our PhD economist).

If you're a mission-driven Data Scientist with a solid statistics foundation and are comfortable working in Python and SQL (R is a plus) on large, cloud-based datasets (Snowflake), this is the role for you.

While remote candidates across the US will be considered, our preferred candidate will be located in the Madison, WI area and work a hybrid schedule based out of Polco’s headquarters office.

Key Responsibilities

• Maintain and run Polco’s recurring data processes, including GPAL and other analytic databases (data ingests, cleaning, dataset refreshes), survey weighting and benchmarking, and periodic model updates.
• Build and improve statistical and predictive models using GPAL and our other databases (for example, our customer renewal model), and adapt existing models as our needs change.
• With mentorship from Polco leadership, take on advanced client analytics projects—including impact and causal-inference studies—and communicate results clearly to internal and external stakeholders through written, in-person, and virtual presentations.
• Partner with our Engineering Team to automate data workflows (ingest, cleaning, analytics, dashboards) and make statistical and AI tooling more accessible across the company.
• Collaborate with our Marketing, Sales, Customer Success, and Survey Research Teams on internal analytics like renewal models.
• Keep clear, organized, and professional documentation so your work is reproducible and transferable across the team, and contribute to Polco’s online reporting tools and internal data apps.

Skills & Requirements

• Bachelor's degree or equivalent experience in a quantitative field grounded in statistics (data science, statistics, economics, or similar). A graduate degree will be helpful, but not required.
• 2+ years of applied, non-academic industry experience in data science or quantitative analysis. A strong applied-project or capstone portfolio can offset part of this.
• Proficiency in Python and SQL (required).
• Working knowledge of R, or willingness to read and learn it as some of our existing tools and internal apps are written in R.
• A solid statistics foundation and genuine interest in causal inference and model building. Deep causal-inference expertise is not required (we'll mentor it), but the aptitude and curiosity to learn it are mandatory.
• Experience building with agentic AI tools (e.g., Claude, Codex)—not just using them, but orchestrating them to run analyses, develop reusable workflows and skills, and extend what you can do statistically beyond what you could hand-code alone.
• Strong written and verbal communication skills, including explaining technical work to non-technical stakeholders.
• Experience working in ambiguity and excitement about moving at startup pace—you like bringing structure to messy, open-ended problems and adapt well when priorities shift.
• Highly organized, detail-oriented, and able to manage multiple projects with minimal oversight.

Nice-to-have Experience

• Survey research, public-sector, or civic-data experience.
• Strong data-visualization skills and a 'storytelling with data' sensibility.
• Experience automating or scaling data workflows in the cloud (Snowflake, etc.).
• Exceptional benefits package including dental, medical, and vision coverage.
• Hybrid work environment if located in the Madison, WI area; 100% remote if elsewhere.
• Flexible work hours, 15 company holidays, and generous paid time off.