• Job Description

  Req#: REQ-032804

  
  The Equity Data Quality Lab group is looking for a knowledgeable, enthusiastic, creative, and results-driven candidate with 10+ years of experience in equity data to join its Global Quality & Process Engineering Team. The team’s mandate is to be the experts in the field of equity data, whom our external and internal clients can trust to provide intelligent, valuable, and timely solutions improve the data quality. To this end as a Financial Data Analyst you will work with content researchers, product consultants, business managers, product managers, project managers, developers, operation team leaders, quality assurance analysts and client/third-party stakeholders to define, manage and implement high quality and timely projects focused on equity data quality particularly covering publicly traded instruments like stocks, debts, options, warrants, splits, and stocks dividends. You will work in a global environment, managing stakeholders in multiple regions.

  • Serve as a financial data expert for companies listed on global exchanges
  • Ideate & build next generation of data science driven proactive quality checks
  • Work closely with multiple global & local teams across various functions and participate regularly in global calls and meetings
  • Should be able to conduct independent audits to determine the data quality
  • Understand and frame quality checks around data quality & extensively working with the data engineers & statisticians to create & maintain the data quality
  • Provide expertise on complex calculations of multiple, historical multiple, total returns from a client perspective
  • Understand and frame policies around different derived & calculated data points with the other stakeholders
  • Develop new tools and capabilities to perform data quality analytics independently, including the use of statistical and machine learning techniques
  • Build and maintain framework to research, manage and timely resolution Data Collection/Computations and Client (both internal & external) queries
  • Conduct and organize quality improvement training sessions
  • Develop and Maintain client friendly documents/manuals/quality matrices.
  • Assist in promoting LEAN Six Sigma tools and methodologies as an analyst framework for assessing the root cause of issues and improving processes

  Master’s degree in finance/Statistics/Mathematics with an exceptional academic record
  • CFA, CPA, CA (completed) preferred
  • 10 + years of professional work experience at specialist/senior/principal/lead analyst
  • Practitioner level understanding of Data Cleaning, Data Management Tools
  • Intermediate level understanding Computational methodology, and Programing (Python/SQL/PostgreSQL)
  • Strong communication skills, people, and project management skills
  • Keen in financial research, and passionate about investing & data management
  • Good analytical skills to research and analyze information to aid in decision making
  • Entrepreneurial skills i.e., able to take the initiative and work without detailed guidance or supervision

  • Deep Knowledge of capital structure shares, split, stock dividend, rights, warrants issue etc.
  • Experience working with tools such as Morningstar Direct, Indices, Bloomberg, Capital IQ, Factset, Refinitiv, etc. on capital structure data
  • Familiar with portfolio analytics / portfolio management tool,
  • Experience building or maintaining data quality at a bank or data vendor or research firm, portfolio manager, index provider will be a plus
  • Experience with managing & identifying data quality issues using cutting edge anomaly detection technologies
  • Intermediate level of knowledge in working with databases (SQL) or PostgreSQL along with Python and willingness to grow these skills

  Morningstar Is Equal Opportunity Employer.

  I10_MstarIndiaPvtLtd Morningstar India Private Ltd. (Delhi) Legal Entity

• About the company

  Morningstar, Inc. is an American financial services firm headquartered in Chicago, Illinois and was founded by Joe Mansueto in 1984.

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