Job Description

Job Title: Quantitative Analyst, Quantitative Research team, MumbaiThe Group: Morningstar\xe2\x80\x99s Quantitative Research Group creates independent investment research and data-driven analytics designed to help investors and Morningstar achieve better outcomes by making better decisions. We utilize statistical rigor and large data sets to inform the methodologies we develop. Our research encompasses hundreds of thousands of securities within a large breadth of asset classes including equities, fixed income, structured credit, and funds. Morningstar is one of the largest independent sources of fund, equity, and credit data and research in the world, and our advocacy for investors\xe2\x80\x99 interests is the foundation of our company.The Role: As Quantitative Analyst, Model Validation you would be involved in development of 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 Statistical, Machine Learning, AI and built on massive amounts of Financial datasets. Often, these services must be integrated into Morningstar\xe2\x80\x99s platform of financial products, such as Direct, so that our clients can use these software tools in the investment decision-making process.We are looking for an individual who possesses strong technical skills, problem solving capability, consulting 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 is based on Mumbai location under Quantitative Research team.Responsibilities:

• Performing independent model validation and review of all Quant models (Risk Models, Morningstar Equity/Fund Ratings) and back end data points.
• E2E verification (data, models) for a variety of analytics and machine learning/AI projects.
• Checking stability, conceptual soundness, model assumptions, mathematical, statistical logic, etc.
• Liaise between business, technical and modeling teams, senior management, and governance committees to build efficient model verification frameworks.
• Develop codes in Python, SQL or similar languages and interface with Morningstar\xe2\x80\x99s big 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
• Supporting model runs in model development process, research new methodologies.

Requirements:

• BS degree in engineering, computer science, statistics, mathematics or equivalent practical experience
• Minimum of 2- 4 years of working experience of Python, databases and SQL in analyzing/ building financial models preferably in a FinTech environment.
• Knowledge of quantitative (econometrics, statistics, mathematics)
• Quantitative/statistical skills in areas like Regression analysis, Time series Forecasting, Machine learning, exploratory, descriptive analytics etc.
• Knowledge of AWS, machine learning, Tableau, mathematical & numerical computation Python packages and artificial intelligence is a plus
• Familiarity with mutual fund, fixed income, and equity data is a plus
• Progress towards a CFA is a plus
• Intellectual curiosity for the world of quantitative research

Morningstar is an equal opportunity employer.036_MstarResearchLLC Morningstar Research Services LLC Legal EntityI10_MstarIndiaPvtLtd Morningstar India Private Ltd. (Delhi) Legal EntityMorningstar\xe2\x80\x99s hybrid work environment gives you the opportunity to work remotely and collaborate in-person each week. We\xe2\x80\x99ve found that we\xe2\x80\x99re at our best when we\xe2\x80\x99re 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\xe2\x80\x99ll have tools and resources to engage meaningfully with your global colleagues.

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