Senior Principal Quantitative Analyst

Senior Principal Quantitative Analyst

Managed Investment Data (MID)

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.

Director, Quality & Transformation

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.

Morningstar is an equal opportunity employer.

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