Quantitative Data Engineer & Research Analyst

• 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 #J-18808-Ljbffr