Director of Model Validation, Analytics

About the role: As Director of Model Validation, Analytics you would develop and implement model validation frameworks for approved research products from prototype phase to a fully-fledged, scalable, and client-facing service. These research products leverage deep principles of Statistics, Machine Learning, AI and are built on massive amounts of financial datasets.These services must be integrated into Morningstar's platforms and support the full breadth of Morningstar products from software tools to data feeds to APIs to indexes.
We are looking for an individual who possesses strong Econometric knowledge coupled with technical skills and leverage them to build efficient model verification frameworks for evolving FinTech solutions. Alongside the person should have a passion for investment research. This position reports to the Head of Product Management, Analytics and will work closely with analytical teams support risk analytics, Managed Product and Equity Ratings, and Portfolio & Financial Planning.
Job responsibilities:

• Consult and guide governance councils (analytics, ratings, and AI) as it relates to quality, model selection, and approvals. Create process for logging, and create quarterly report cataloguing all errors for the Executive Leadership Team.
• Assist in RFPs and onboarding for new clients who need help validating our models
• Ensure independent model validation and review of all Analytics models (Risk Models, Morningstar Equity/Fund Ratings) and capabilities, performing several of these model validations and reviews as an individual contributor
• Develop and improve Model Validation framework for all models working with engineering, product, and analysts.
• Create consistent methods, processes, and tools for escalations, errors, and triaging
• Work with Research Operations to create and maintain documentation for periodic model validation/ methodology review
• Manage 10+ person Model Validation team across global locations, and support model validation activities and impact analyses in partnering teams without direct management responsibilities
• E2E verification (data, models) for a variety of analytics and machine learning/AI projects.
• Check stability, conceptual soundness, model assumptions, mathematical, statistical logic, etc.
• Create consistent methods, processes, and tools for escalations, errors, and triaging
• Develop codes in Python to automate processes to interface with Morningstar's databases to support model validation. Automate process to reduce human intervention.
• Build rich dashboard to support Quality Checks(interactive/automated/visual) that improve the interpretability of predictive models and underlying data
• Support model runs in model development process
• Conduct independent research on new methods or technologies

Qualifications:

• 5 - 10 years experience in analyzing/ building financial models preferably in a FinTech environment.
• 5+ years of Managing resources across multiple locations
• Deep knowledge in Quantitative methods / econometrics/ statistics.
• Strong in Regression analysis, Time series Analysis, optimization.
• Knowledge of Risk Models and Optimization algorithms.
• Good working knowledge of Python and SQL, Machine learning, exploratory data analysis
• Knowledge of AWS, Tableau and ML/ DL algorithms is a plus.
• Strong candidates should have a graduate degree in computer science, statistics, econometrics, mathematics, computational finance, or similar

001_MstarInc Morningstar Inc. Legal Entity
Morningstar's hybrid work environment gives you the opportunity to work remotely and collaborate in-person each week. We've found that we're at our best when we're purposely together on a regular basis, at least three days 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.