Our client, a IT Services and Consulting company, is looking for a Quantitative Research Analyst (Data Modeling & Imputation) for their Chicago, IL/Boston, MA/Hybrid location. Responsibilities:


+ 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

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