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At PwC, our people in risk and compliance focus on maintaining regulatory compliance and managing risks for clients, providing advice, and solutions. They help organisations navigate complex regulatory landscapes and enhance their internal controls to mitigate risks effectively.

At PwC, our people in risk and compliance focus on maintaining regulatory compliance and managing risks for clients, providing advice, and solutions. They help organisations navigate complex regulatory landscapes and enhance their internal controls to mitigate risks effectively.

We are seeking a seasoned Traded Risk Practice Leader to drive growth, delivery excellence, and capability development across Market Risk and Counterparty Credit Risk (CCR) domains. The role blends domain leadership with business growth responsibilities which include shaping strategy, strengthening client relationships and expanding the firm’s Traded Risk franchise across global financial institutions.

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.

At PwC, our people in data and analytics focus on leveraging data to drive insights and make informed business decisions. They utilise advanced analytics techniques to help clients optimise their operations and achieve their strategic goals. In data analysis at PwC, you will focus on utilising advanced analytical techniques to extract insights from large datasets and drive data-driven decision-making. You will leverage skills in data manipulation, visualisation, and statistical modelling to support clients in solving complex business problems.

Enhancing your leadership style, you motivate, develop and inspire others to deliver quality. You are responsible for coaching, leveraging team member’s unique strengths, and managing performance to deliver on client expectations. With your growing knowledge of how business works, you play an important role in identifying opportunities that contribute to the success of our Firm. You are expected to lead with integrity and authenticity, articulating our purpose and values in a meaningful way. You embrace technology and innovation to enhance your delivery and encourage others to do the same.

Examples of the skills, knowledge, and experiences you need to lead and deliver value at this level include but are not limited to:

• Analyse and identify the linkages and interactions between the component parts of an entire system.
• Take ownership of projects, ensuring their successful planning, budgeting, execution, and completion.
• Partner with team leadership to ensure collective ownership of quality, timelines, and deliverables.
• Develop skills outside your comfort zone, and encourage others to do the same.
• Effectively mentor others.
• Use the review of work as an opportunity to deepen the expertise of team members.
• Address conflicts or issues, engaging in difficult conversations with clients, team members and other stakeholders, escalating where appropriate.
• Uphold and reinforce professional and technical standards (e.g. refer to specific PwC tax and audit guidance), the Firm’s code of conduct, and independence requirements.

At PwC, our people in data and analytics focus on leveraging data to drive insights and make informed business decisions. They utilise advanced analytics techniques to help clients optimise their operations and achieve their strategic goals. In data analysis at PwC, you will focus on utilising advanced analytical techniques to extract insights from large datasets and drive data-driven decision-making. You will leverage skills in data manipulation, visualisation, and statistical modelling to support clients in solving complex business problems.

Focused on relationships, you are building meaningful client connections, and learning how to manage and inspire others. Navigating increasingly complex situations, you are growing your personal brand, deepening technical expertise and awareness of your strengths. You are expected to anticipate the needs of your teams and clients, and to deliver quality. Embracing increased ambiguity, you are comfortable when the path forward isn’t clear, you ask questions, and you use these moments as opportunities to grow.

Skills

Examples of the skills, knowledge, and experiences you need to lead and deliver value at this level include but are not limited to:

• Respond effectively to the diverse perspectives, needs, and feelings of others.
• Use a broad range of tools, methodologies and techniques to generate new ideas and solve problems.
• Use critical thinking to break down complex concepts.
• Understand the broader objectives of your project or role and how your work fits into the overall strategy.
• Develop a deeper understanding of the business context and how it is changing.
• Use reflection to develop self awareness, enhance strengths and address development areas.
• Interpret data to inform insights and recommendations.
• Uphold and reinforce professional and technical standards (e.g. refer to specific PwC tax and audit guidance), the Firm’s code of conduct, and independence requirements.