Quantitative Research Analyst (Data Modeling & Imputation)

Job Title

Quantitative Research Analyst (Data Modeling & Imputation)

Location: Chicago IL or Boston MA (Hybrid)

Job Summary

STAFFXPERT LLC is seeking a Quantitative Research Analyst (Data Modeling & Imputation) on behalf of our client in Chicago IL or Boston MA. This role is ideal for an experienced quantitative professional with a strong background in data science quantitative research or financial data engineering. The successful candidate will play a key role in building scalable data pipelines transforming complex datasets and applying advanced statistical techniques to ensure high-quality reliable data for research and analytical initiatives.

Key Responsibilities

• Design develop and maintain scalable end-to-end data pipelines for structured and unstructured datasets.

• Perform large-scale data wrangling transformation cleansing and integration across diverse data sources.

• Develop data normalization and reconciliation processes across complex hierarchies including entities business segments and geographies.

• Write efficient maintainable and reproducible Python and SQL code for large-scale data processing.

• Apply advanced missing-data handling and imputation techniques including cross-sectional inference time-series interpolation and model-based approaches.

• Analyze and process complex real-world datasets with inconsistent incomplete or noisy data.

• Ensure data quality accuracy and consistency through scalable and repeatable analytical workflows.

• Collaborate with cross-functional teams to support quantitative research and data-driven decision-making.

Required Qualifications

• 12 years of experience in quantitative research data science financial data engineering or a related analytical field.

• Strong expertise in large-scale data wrangling transformation and preprocessing.

• Advanced proficiency in Python including pandas and NumPy.

• Strong SQL skills with experience writing optimized queries for large datasets.

• Hands-on experience building and maintaining scalable data pipelines.

• Proven experience with missing data methodologies and statistical imputation techniques.

• Strong foundation in statistics econometrics and quantitative analysis.

• Demonstrated ability to work with complex messy real-world datasets and deliver high-quality analytical solutions.

Preferred Qualifications

• Experience working with financial or market data.

• Familiarity with entity resolution hierarchy management and data reconciliation techniques.

• Knowledge of scalable data processing and performance optimization.

• Experience supporting quantitative research or advanced analytical modeling initiatives.