Quantitative Analyst / Data Quality Analyst

Role Description

The Quantitative Analyst / Data Quality Analyst is responsible for applying quantitative methods while ensuring the integrity, accuracy, and reliability of data used for analysis and decision-making. This role combines advanced analytical modeling with strong data governance practices to support high‑quality, data‑driven insights.

The position involves developing statistical models, performing quantitative analysis, and working with large datasets to identify patterns, trends, and relationships. At the same time, the role ensures that data is clean, consistent, and validated through rigorous data quality checks and monitoring processes.

In addition, the role includes identifying data discrepancies, conducting root cause analysis, and implementing solutions to improve data quality and reliability. The Quantitative Analyst / Data Quality Analyst collaborates with data engineers, analysts, and business stakeholders to maintain high data standards and support analytical initiatives.

The role also involves preparing reports, dashboards, and documentation that communicate both analytical findings and data quality metrics. By integrating quantitative analysis with data quality management, this position ensures that insights are both accurate and actionable.

The role requires strong technical expertise, attention to detail, and the ability to handle complex datasets. This position plays a key role in strengthening analytical capabilities while maintaining trust in data across the organization.

Qualifications

• Bachelor’s or Master’s degree in Mathematics, Statistics, Data Science, Computer Science, or a related field.
• Strong knowledge of statistical analysis, quantitative modeling, and data validation techniques.
• Proficiency in programming languages such as Python, R, or SQL.
• Experience working with large datasets and data quality management practices.
• Strong analytical and problem‑solving skills.
• Attention to detail with a focus on data accuracy and consistency.
• Familiarity with data governance frameworks and data quality tools.
• Ability to interpret complex data and communicate insights clearly.
• Strong documentation and reporting skills.
• Ability to collaborate effectively with cross‑functional teams.

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