Senior Data Scientist

 

SENIOR DATA SCIENTIST

DART PROGRAM

 POSTED:9/3/2025

 

ABOUT CJA 

The New York City Criminal Justice Agency (CJA) is a not-for-profit service and research organization that operates in partnership with the New York City Mayor’s Office of Criminal Justice.  CJA is the City’s main pretrial services agency, combining operations, pilot projects, and research under one roof.  CJA utilizes procedural justice practices to provide pretrial services to over 100,000 arrested annually in New York City. Information collected about these arrestees and subsequent case processing is maintained in the agency’s internal and externally shared database systems, which are used to conduct descriptive and evaluation research on arrestee characteristics, case processing and court outcomes, and on issues and potential reforms to criminal justice policy in New York City. CJA’s programs operate in the criminal courts and detention facilities 24 hours a day seven days a week within the 5 boroughs of NYC, employing over 300 employees, citywide. 

PROGRAM SUMMARY 

DART – We lead research and analytics that turn CJA’s unparalleled justice system data into insights that drive policy and practice. Drawing on over 100,000 annual face-to-face interviews and comprehensive data feeds from police, courts, and corrections, we analyze complex trends, evaluate emerging policies, and apply causal techniques to assess the impact of policy and applied interventions. Through rigorous analysis, compelling visualizations, and impactful publications, we illuminate the workings of New York City’s justice system and advance new lines of inquiry to shape a fairer, more effective system.

POSITION SUMMARY

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.

PRIMARY 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.
  
  

QUALIFICATIONS

• 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, includi