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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

• Strong foundation in quantitative finance, econometrics, and applied statistics.
• Deep understanding of financial instruments, fund structures, and performance modeling.
• Proven ability to work with large-scale, structured and unstructured data.
• Excellent analytical, problem-solving, and statistical reasoning skills.
• Strong stakeholder management, communication, and presentation skills.
• Ability to work in a cross-functional, fast-paced environment, and lead through influence.

 

 

Desired Candidate Profile

• Master’s degree in Statistics, Mathematics, Financial Engineering, Data Science, or Quantitative Finance.
• Professional certifications such as CFA, FRM, CQF, or Six Sigma Black Belt preferred.
• 10+ years of experience in quantitative analytics, model validation, or data quality engineering within financial services, asset management, or fintech.
• Expertise in Python, R, SQL, and familiarity with tools such as MATLAB, SAS, or TensorFlow.
• Experience in AWS ecosystem (S3, RDS, Glue, Athena) and modern data quality platforms.
• Hands-on experience with AI/ML frameworks (scikit-learn, PyTorch, TensorFlow) for anomaly detection and predictive data correction.
• Familiarity with data governance and regulatory standards (GDPR, SEC, ESMA, MiFID).
• Proficiency in Lean, Agile, and automation-first approaches for process improvement.
• Entrepreneurial mindset with a passion for innovation and scalability.
• Strong leadership, mentorship, and collaboration abilities.
• Flexible to adapt to evolving data and technology landscapes.

 

Key Competencies

• Statistical Expertise: Deep proficiency in hypothesis testing, regression modeling, and time-series forecasting.
• AI/ML Integration: Building and deploying predictive quality and anomaly detection models.
• Automation Mindset: Experience with data pipelines, ETL automation, and observability frameworks.
• Data Governance: Comprehensive understanding of metadata management, lineage, and auditability.
• Business Acumen: Translating technical insights into actionable business intelligence.
• Leadership: Guiding teams through analytical rigor, innovation, and continuous improvement.

Please see job role.

Please see job role.

The key job responsibilities will be to:

• Work on consulting projects related to financial instrument modeling, model review, securities pricing, and risk management including support for regulatory compliance.
• Develop or validate equity, FX, and hybrid based exotic pricing models with a focus on conceptual assessment and assumptions testing.
• Perform quantitative analysis focused on Profit Attribution Analysis (PAA), Stress Testing and Non- modellable Risk Factors (NMRFs) for the models being validated.
• Assess valuation methodology for fixed income instruments and derivatives on interest rates, foreign exchange, equity, and credit.
• Design, implement and critique on calibrations of parametrized valuation models such as Black Scholes, Hull & White, SABR, Heston, etc.
• Assess IPV methodology for external clients covering products across all asset classes.
• Assist client in Advisory projects around the evolving issues e.g., XVA, IBOR Transition, etc. that affect the valuation of derivatives and structured products.

Qualifications

Must Have Skills/Project Experience/Certifications:

• 1-4 years of experience with quantitative analysis technical tools such as Python, R, MATLAB, SAS, etc.
• Familiarity with valuation of fixed income instruments, derivatives on interest rates, foreign exchange, equity, and credit. Understanding of financial derivatives, stochastic calculus, and numerical techniques for derivatives pricing (Monte Carlo / Finite Difference).
• Familiarity with various quantitative measures related to Market Risk (e.g., VaR, Expected Shortfall, etc.) and Counterparty Credit Risk (e.g., Expected Exposure, Expected Potential Exposure, etc.)
• Familiarity with tools like Bloomberg, Refinitiv, Murex, etc. is a plus.
• Experience in model validation like Asset Liability Management, Economic Capital Models, etc. is a plus.
• Understanding of financial regulations (like FRTB), products or financial processes is a plus
• Ability to explain difficult financial modeling/valuation concepts to diverse audiences and to experts at various clients.
• Related bank/consulting experience is a plus.

Join the R&D Product Management organization, to work as a product owner of complex regulatory module powered by super advance Calypso software platform that supports cross asset risk and pricing and is capable of delivery high performance.

Role Responsibilities –

As a Lead Product Manager, your focus will be on crafting and improving software product to meet the customer requirements and regulatory changes. Besides working closely with your colleagues in Mumbai, you will also work closely with Nasdaq teams in other countries.

• Research about the current capabilities of product and find avenues to further improve the product on a continuous basis
• Generate detailed functional specifications for new feature to be delivered on the product.
• Review issues raised by customer/Product support team and provide timely advice and resolutions.
• Keep track of changing regulatory landscape and update the product accordingly.
• Analyze product performance and come up with ideas to improve the same
• Come with ideas to improve the product coverage and efficiency
• Liaise and work closely with Developers and Quality Analyst to ensure seamless product delivery cycle

We expect you to have: (Minimum Qualifications)

• Experience Level 10-12 years
• Primary Skills – Financial Risk Management, Market Risk, FRTB, Capital Markets
• Soft Skills – Social skills, writing skills
• Education Qualification – MBA Finance/Bachelor in Engineering with FRM/CFA/CQF charter

It Would Be Phenomenal If You (Preferred Qualifications)

• FRM/CFA/CQF Charter holder
• Experience in pricing and valuation of exotic financial derivative products
• Market Risk Management process and regulations
• Project Management and Execution

Primary Responsibilities include, but are not limited to:

• Development, enhancement and maintenance of portfolio market risk models like IRC, CRM and DRC to ensure ongoing appropriateness and adaptations to new regulations
• Contribution to key regulatory deliverables and programs as well as analysis and interpretation of key regulatory requirements.
• Ensure robust implementation and timely completion of ongoing monitorings and evaluation of market risk models, review existing models to ensure they remain fit for purpose and make improvements where necessary.
• Collaborate closely with the model validation team to understand validation findings and remediate any identified issues
• Collaborate with the other teams (data, IT, change management) to ensure that model changes are appropriately implemented.
• Document models and associated developmental analysis; present results to partners and stakeholders
• Manage, guide and train junior members of the team

Skills Required

What you’ll bring to the role:

• 9+ years of work experience in Quantitative modeling, Risk Management, Algorithmic trading, Global markets, or any other quantitative/Data Science field.
• Deep understanding of quantitative risk including good knowledge of statistical modelleing, financial products and their risk representation.
• Demonstrable experience in delivering enhancements to risk models
• Excellent mathematical, analytical, problem solving and troubleshooting skills
• Strong programming skills and demonstrable experience in coding numerical methods and algorithms, data analysis and manipulation
• Advanced knowledge of at least one prototyping programming language (preferably Python) and preferably experience/knowledge of professional development concepts and technologies and modern development toolchain
• Experience in people management is required – the candidate should be able to support and motivate the team
• The ability to effectively communicate with a wide range of stakeholders, both written and verbally
• An interest in working in a fast-paced environment, often balancing multiple high priority deliverables.

Required Qualifications

• Postgraduate/ Advanced degree in Quantitative Finance, Mathematics, Econometrics, Engineering, or other Quantitative subjects.

Desirable Skills

• FRM, CFA, CQF certification is an advantage.