Opportunity Description
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
...
+ 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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