Econometric Data Analyst: Litigation & Regulatory Analytics

Cornerstone Research; Boston (MA); Hybrid; USD 110,000 - 135,000; Full time

Benefits offered by this job

Visa support

Starting bonus

Discretionary bonuses

Competitive benefits

Job summary

Cornerstone Research seeks a Data Analyst to support complex litigation, regulatory investigations, and financial disputes with rigorous data-driven insights. You will join case teams, contribute across all project phases, and help deliver reproducible analyses and client-ready outputs.

This early-career role emphasizes building technical capability within the Data Science Center, with a hybrid work model requiring at least 50% in-office presence in your local office.

Qualifications

• BA/BS or MA/MS in a quantitative field; strong academic performance expected.
• 1-3 years of relevant work experience involving data analysis or programming.
• Strong ability to produce clean, well-documented outputs.
• Experience with SQL for data extraction and databases.
• Proficiency in Python or R and knowledge of econometrics or statistics.
• Excellent written and verbal communication; team collaboration.
• Experience handling large datasets (terabytes).

Responsibilities

• Perform exploratory and econometric analyses on case data.
• Own end-to-end data workflows: ingestion, cleaning, transformation, validation.
• Build and maintain data infrastructure and reproducible pipelines.
• Translate case needs into structured, documented data outputs.
• Uphold coding standards and serve as data reference for teams.
• Lead escalation when technical issues arise.

Skills

SQL

Python

R

Bash/CLI/Git

Data analysis

Econometrics

Communication

Education

BA/BS or MA/MS in a quantitative field

Tools

Redshift

S3

Databricks

Job description

Cornerstone Research seeks a Data Analyst to support complex litigation, regulatory investigations, and financial disputes with rigorous data-driven insights. You will join case teams, contribute across all project phases, and help deliver reproducible analyses and client-ready outputs.

This early-career role emphasizes building technical capability within the Data Science Center, with a hybrid work model requiring at least 50% in-office presence in your local office.