Senior Quantitative Analyst

Morningstar

Mumbai

1d ago

Job Description

The Group : Morningstar’s 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’ interests is the foundation of our company.

The Role : As a Senior Quant Analyst, 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’s 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 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 Senior Manager, Quantitative Research of the Quantitative Research team.

Responsibilities :

Performing independent model validation and review of all Quant models (Risk Models, Morningstar Equity / Fund Ratings / Optimizer) and back-end data points.

Guide and build the framework for validation each model that is developed

Manage the testing design and execution, interpreting and presenting the results

Checking stability, conceptual soundness, model assumptions, mathematical, statistical logic, etc.

E2E verification (data, models) for a variety of analytics and machine learning / AI projects.

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’s 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 :

3 6 years’ experience in analyzing / building financial models preferably in a FinTech environment

Hold a Masters degree in a quantitative field, e.g. Mathematics, Physics, Engineering, Finance, Economics with experience in financial modelling and / or model validation

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

Good to have : Knowledge of Machine learning models, Exploratory data analysis

Knowledge of AWS, Tableau and ML / DL algorithms is a plus

Morningstar is and equal opportunity employer

About Us

DBRS Morningstar is a global credit ratings business, currently with 700 employees in eight offices globally. Formed through the July 2019 acquisition of DBRS by Morningstar, Inc.

the ratings business is the fourth-largest provider of credit ratings in the world.

DBRS Morningstar is committed to empowering investor success, serving the market through leading-edge technology and raising the bar for the industry.

DBRS Morningstar is a market leader in Canada, the U.S. and Europe in multiple asset classes.

DBRS Morningstar rates more than 2,600 issuers and 54,000 securities worldwide and is driven to bringing more clarity, diversity of opinion, and responsiveness to the ratings process.

DBRS Morningstar’s approach and size provide the agility to respond to customers’ needs, while being large enough to provide the necessary expertise and resources.

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