As a Senior Data Scientist, you will deliver advanced analytics that drive policy and practice. You’ll combine expertise in causal inference—including RCTs and quasi-experimental methods—with policy relevant data analysis, predictive modeling, and modern machine learning techniques.
You’ll collaborate with DART and IT staff to build pipelines and scalable workflows, conduct exploratory and statistical analyses, and translate complex findings into intuitive and actionable products—policy briefs, interactive dashboards, and applied ML tools. You’ll collaborate with a supportive team to drive projects from scoping through delivery.
Key roles and responsibilities
- Analytics & Data Science – Conduct exploratory data analysis and build descriptive and predictive models to support policy and practice. Create reproducible workflows in Python, R, and SQL, and maintain well-documented Jupyter Notebooks. Develop dashboards, visualizations, and data tools to make analyses accessible to technical and non-technical stakeholders.
- Causal Research & Evaluation – Design and oversee rigorous causal studies, including RCTs and quasi-experimental designs. Define evaluation frameworks, identify appropriate counterfactuals, and ensure methodological rigor in estimating policy and operational impacts. Conduct power and sample size calculations to optimize the design of RCTs and quasi-experimental studies. Translate findings from causal analyses into actionable recommendations that inform policy and practice.
- Research Dissemination and Communication – Deliver policy briefs, presentations, and interactive dashboards that translate complex findings into actionable, decision-ready evidence.
- Partner with city agencies, nonprofits, and justice system stakeholders to scope projects and align research with operational needs.
- Support public and stakeholder engagement by presenting results at conferences, policy forums, and cross-agency working groups.
Experience
- 5+ years of experience in applied data science, analytics, or research roles, ideally in policy or civic tech. A strong portfolio of self-directed analytic work is expected. Experience in the justice system is a plus.
- Education: A postgraduate degree (Master’s or PhD) in statistics, economics, data science, computational social science, or a related quantitative field.
- Technical Expertise:
- Strong proficiency in Python or R for data manipulation, analysis, and modeling (Python preferred).
- Experience conducting causal inference and advanced econometric analyses, including RCTs, DiD, IV, ITS, matching, and synthetic control.
- Advanced statistical techniques and modern machine learning methods for predictive modeling.
- Experience working with relational databases (e.g. Microsoft SQL, PostgreSQL) and writing complex SQL queries.
- Expertise in data wrangling and cleaning, including handling messy, incomplete, or complex administrative datasets
- Proven ability to translate complex analyses into clear, actionable insights for technical and non-technical stakeholders.
- Experience integrating external data from APIs and common data formats like JSON, CSV, and Parquet
- Strong data storytelling skills, with experience creating or supporting compelling visualizations, dashboards, and policy briefs.