Data Scientist

About the job

The Group: Morningstar, Inc.’s mission is to empower investor success. We were founded on the simple idea that when people have good investment information, they make better choices that lead to better outcomes. The Investment Management group consists of our Managed Portfolios and Workplace solutions teams. Within Morningstar Investment Management, LLC, the Workplace group offers a range of retirement solutions, including managed accounts, custom models, and advice service by acting in a fiduciary capacity or as an independent financial expert, as defined by ERISA: IFE, 3(28), or 3(21) capacity. The flagship product is our Morningstar Retirement Manager which provides personalized advice on how much to save for retirement, asset allocation advice, and builds portfolios for individual investors. The Workplace team consists of the investment management team, the research team, the advice engines team, the operations team, and the client services team. The goal of these teams is to work together to provide investment solutions for the individual investor’s retirement goals.
The Role:
Morningstar is seeking a Data Scientist to join our team of product management professionals. This person will work across our Managed Accounts platforms, Wealth Forecasting Engine (WFE), Automated Portfolio Construction and Retirement Planning tools. You will collaborate with research, development, and marketing teams to ensure successful product support & enhancements. If you are passionate about using your statistical skills in the financial domain, we invite you to apply for this exciting opportunity.
This position reports to Quantitative Research Manager, Advice and Financial Planning. Key Responsibilities:

• Harness the capabilities of machine learning and generative AI to develop cutting-edge solutions that enhance the troubleshooting and problem-solving capabilities of our current products and methodologies.
• Leverage statistical and financial expertise in analytics projects to drive insights and support data-driven decision-making.
• Implement automated workflows, develop dashboards, and streamline processes to enhance operational efficiency.
• Integrate proprietary research and financial planning concepts into a global set of advice engines by working closely with Morningstar research, product managers, and developers to bring intellectual property and new methodology to market.
• Develop an in-depth understanding of the Wealth Forecasting Engine and Automated Portfolio Construction tool, its underlying methodologies and implementations.
• Support internal and external clients through product demonstrations, troubleshooting, methodological proofs, and timely communication.
• Create and implement automated processes leveraging cloud computing solutions like AWS, utilizing Python for scripting and workflow orchestration.
• Build dashboards to support Quality Checks(interactive/automated/visual) that improve the interpretability of Quant models.

Requirements:

• Proven experience (2-4 years) implementing data science solutions, ideally within the financial domain.
• Candidates with experience in developing or working with state-of-the-art Generative AI solutions are highly desirable.
• Proficiency in Python, R, or MATLAB and Hands-on experience with AWS would be a plus.
• Demonstrated ability to visualize data using Python/MATLAB/ R/Tableau or experience with interactive frameworks like Dash/Shiny would be a plus.
• A good knowledge of a query language like SQL for data extraction and management is required.
• Possessing a robust foundation in machine learning and the practical skillset to leverage this knowledge by developing and deploying code-based solutions.
• Understanding of both business and technical requirements, and the ability to serve as a conduit between product, research, technology, and external clients.
• Excellent English-language oral and written communication.
• Bachelor’s degree in finance, economics, mathematics, engineering, computer science or related field is required. A Master’s degree or CFA are all highly desired.

Morningstar is an equal opportunity employer. I10_MstarIndiaPvtLtd Morningstar India Private Ltd. (Delhi) Legal Entity

If you receive and accept an offer from us, we require that personal and any related investments be disclosed confidentiality to our Compliance team (days vary by region). These investments will be reviewed to ensure they meet Code of Ethics requirements. If any conflicts of interest are identified, then you will be required to liquidate those holdings immediately. In addition, dependent on your department and location of work certain employee accounts must be held with an approved broker (for example all, U.S. employee accounts). If this applies and your account(s) are not with an approved broker, you will be required to move your holdings to an approved broker.

Morningstar's hybrid work environment gives you the opportunity to collaborate in-person each week as we've found that we're at our best when we're purposely together on a regular basis. In most of our locations, our hybrid work model is four days in-office 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.