Senior Principal Quantitative Analyst

Position : Senior Principal Quantitative Analyst

Department : Managed Investment Data (MID) – Quality & Transformation

No of Positions : 1

Shift : General Shift

Job Description

The Senior Principal Quantitative Analyst plays a critical role in ensuring the accuracy, integrity, and reliability of quantitative data that powers Morningstar's financial models, analytics, and decision-making processes.

This role is a cornerstone of the Managed Investment Data (MID) program, which collects, standardizes, and enriches global fund data—supporting investors, advisors, and institutions through trusted data and insight.

The analyst will lead quantitative data quality design and implementation, develop AI / ML-based validation frameworks, and collaborate with cross-functional teams to strengthen data governance and model readiness.

This role reports to the Director, Quality & Transformation within the Managed Investment Data team based in Mumbai.

Job Responsibilities

• Lead the design, implementation, and enhancement of quantitative data quality frameworks, encompassing statistical validation and anomaly detection.
• Develop AI / ML-driven predictive quality checks, enabling proactive data error prevention and model trustworthiness.
• Apply advanced statistical methodologies — linear / non-linear modeling, time series analysis, and Bayesian inference — to detect quality drifts and signal inconsistencies.
• Collaborate with quantitative researchers, data scientists, and engineers to ensure data readiness for quantitative models and investment algorithms.
• Create automated, scalable, and auditable data validation pipelines, supporting real-time data monitoring and exception reporting.
• Partner with stakeholders to uphold data governance, privacy, and regulatory compliance standards (MiFID, ESMA, SEC).
• Mentor and guide junior analysts, fostering a culture of excellence, continuous learning, and innovation in quantitative analysis.
• Communicate complex data quality insights and statistical findings in simple terms to senior leadership and non-technical stakeholders.
• Drive innovation through automation, reproducible modeling pipelines, and deployment of ML-based data correction systems.
• Contribute to the modernization of Morningstar's data architecture by integrating data observability, telemetry, and metadata-driven quality measures.

Requirements

Desired Candidate Profile

Key Competencies

Morningstar is an equal opportunity employer.

We celebrate diversity and are committed to creating an inclusive environment for all employees.

Morningstar's hybrid work environment gives you the opportunity to collaborate in-person each week as we've found that we're at our best when we're purposely together on a regular basis. In most of our locations, our hybrid work model is four days in-office each week. A range of other benefits are also available to enhance flexibility as needs change. No matter where you are, you'll have tools and resources to engage meaningfully with your global colleagues.

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Skills Required

Tensorflow, Pytorch, Sas, Sql, Matlab, Python, Aws