Quantitative Research Analyst (Data Modeling & Imputation)

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., 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., Research Data Analyst The Research Data Analyst will conduct data analysis and assist other research team members (students, staff, and investigators) with their analyses and manus…

• 6 days ago +

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.

Job Description: Established nearly two centuries ago, FM is a leading mutual insurance company whose capital, scientific research capability and engineering expertise are solely…