Analysis Skills, Data Management, Data Modeling, Data Processing, Data Quality, Data Sets, Financial Reporting, Python Programming/Scripting Language, Quantitative Analysis, Quantitative Research, Reconciliation, SQL (Structured Query Language)
Role: Quantitative Research Analyst (Data Modeling & Imputation)
Location: Chicago, IL (or) Boston, MA (Onsite from Day 1)
Job Type: W2 Contract
Description:
Build and maintain end-to-end data pipelines across structured and unstructured datasets
Develop imputation frameworks for missing or sparsely reported financial data (e.g., segment-level estimates, coverage gaps, timing mismatches)
Design and implement data normalization and reconciliation logic across overlapping hierarchies (e.g., segments, geographies, entities)
Perform data quality diagnostics, including coverage analysis, bias detection, and stability testing
Partner with researchers to translate raw data into model-ready features
Write efficient, reproducible code in Python and SQL for large-scale data processing
Document methodologies clearly to ensure transparency and repeatability