Jobs at Morningstar

Leads quantitative analysts in developing and launching benchmark, thematic, factor, strategic beta, and multi-asset indexes. Owns the full index lifecycle, including opportunity identification, signal testing, back-testing, methodology design, risk analytics, and launch. Champions AI-enabled research automation, mentors team members, collaborates across research groups, and develops analytical tools, white papers, and client-ready materials.

Leads engineering and data science teams building AI/ML data collection systems for large-scale unstructured data. Provides technical direction across NLP, classifiers, LLMs, MLOps, data pipelines, cloud platforms, security, and system operationalization. Responsibilities include mentoring and hiring talent, overseeing scalable model and pipeline development, collaborating cross-functionally, improving delivery processes, and ensuring reliable, secure, high-performance solutions.

Develop and configure ServiceNow solutions across HRSD, HAM, SAM, ITSM, CMDB, and related modules. Build service catalogs, workflows, integrations, data migrations, reports, dashboards, and automated tests. Collaborate with stakeholders to translate business needs into technical solutions, maintain documentation, ensure platform security and stability, and drive continuous improvements.

Leads and mentors a data engineering team responsible for enterprise data pipelines, models, governance, quality, and platform reliability. Defines the data engineering roadmap, guides cloud architecture decisions, and partners with business and technology leaders. Oversees scalable ETL/ELT workflows using modern data technologies, optimizes performance and costs, and advances AI-enabled analytics capabilities. Builds team effectiveness through hiring, coaching, retention, and performance development.

The Talent Acquisition Operations Analyst optimizes recruiting processes, systems, data integrity, governance, and candidate experience for India. Responsibilities include serving as a Workday Recruiting subject matter expert, gathering requirements, leading testing and deployment, maintaining playbooks, developing reporting needs, resolving process and technology defects, supporting recruiter training, coordinating communications, and assisting with vendor evaluation. The role requires strong talent acquisition operations, analytics, process improvement, stakeholder management, and India recruiting compliance expertise.

Develops innovative investment indexes from ideation through launch, conducting quantitative research, portfolio construction, validation, and analytics. Collaborates with research and product teams, applies statistical and machine learning techniques, and creates white papers, factsheets, presentations, and client materials. The role requires strong investment knowledge, programming and SQL proficiency, communication skills, and experience in quantitative finance or related analytical fields.

Supports structured finance analytics by automating data analysis, document downloads, data storage, reporting, and workflow optimization. Combines data from multiple sources, develops analytics using databases and cloud storage, and contributes to ratings, research, surveillance, and criteria development. The role requires accuracy, organization, teamwork, process improvement, and compliance with company policies.

Lead and manage a development team to design, implement, test, and maintain full-stack .NET-based applications on AWS. Drive architecture and technical decisions, enforce coding standards, collaborate with product and architecture teams, mentor developers, and use Agile practices to deliver features and improve team performance.

Produces recurring fund performance, attribution, risk, and peer comparison reports using Morningstar Direct and Excel. Troubleshoots return discrepancies, validates benchmarks, pricing, indexes, and vendor data, and uploads information to internal applications. Handles performance inquiries, supports GIPS verification, and contributes to portfolio attribution analysis. The role requires strong analytical, quantitative, communication, organization, and problem-solving skills, along with flexibility to support global colleagues during varying hours.

Manage and resolve product ticket issues, prioritize escalations, document workflows, and improve operational processes. Administer investment platform activities including deposits, withdrawals, account maintenance, reporting, reconciliations, corporate actions, and income distributions. Monitor discrepancies, maintain data accuracy and security, coordinate with internal and external stakeholders, and support wealth management operations. Requires strong financial services knowledge, analytical ability, organization, communication, and Excel skills.

Entry-level apprentice supporting data collection, verification, research, and quality control across financial and investment datasets. The role involves responding to internal and client queries, following data methodologies, resolving data issues with cross-functional teams, and meeting productivity, quality, and deadline standards. Structured training is provided during the 6–12 month apprenticeship, with possible early morning, afternoon, evening, and night shifts.

Manages relationships with Indian fund companies and data providers, supports data acquisition channels, promotes Morningstar investment data, and advises clients and internal teams on data methodologies. Identifies market opportunities, monitors industry and regulatory trends, represents client needs, and collaborates globally on database enhancements and data-focused projects.

Conduct quantitative and qualitative credit research on CMBS transactions, including reviewing deal documents, analyzing loan and property performance, identifying risk factors, modeling net cash flows, and preparing portfolio and executive reports. The role supports ratings, research, criteria development, special projects, user acceptance testing, and regulatory compliance while collaborating with operations and technology teams.

Design and maintain automated data quality frameworks, validation controls, monitoring solutions, and reconciliation processes for large-scale financial datasets. The role identifies anomalies, missing or stale data, outliers, and reconciliation breaks; validates data from market-data providers; embeds controls into ETL/ELT pipelines; and supports onboarding of new investment datasets. Advanced Python, SQL, PySpark, financial data testing, profiling, root-cause analysis, and cloud data platform experience are required.

Leads month-end and quarterly close activities for the Americas, ensuring accurate, compliant, and audit-ready financial records. Responsibilities include reviewing financial statements, analyzing variances, preparing reconciliations, supporting GL, AP, AR, billing, revenue, accruals, intercompany, and expense accounting, and advising on complex transactions. The role partners with shared services and cross-functional finance teams while driving standardization, automation, close-cycle improvements, and technology adoption.

Provide L2/L3 production support for financial products and services, troubleshoot application and data issues, manage incidents and service requests, perform root-cause analysis, communicate resolutions, maintain knowledge resources, and collaborate with development teams on production fixes and improvements. The role supports global offices during the US night shift and requires strong technical troubleshooting, SQL, application monitoring, and stakeholder communication skills.

Own daily treasury operations (cash positioning, bank account administration, controls, reconciliations) and lead projects to automate and standardize treasury processes. Partner with Corporate Treasury, local finance, banks, IT and vendors on implementations, testing, and global standardization. Ensure audit-ready controls, resolve banking exceptions, and deliver measurable improvements in reporting and operational efficiency.

Lead month-end and quarterly close activities across general ledger, accounts payable, accounts receivable, billing, revenue, accruals, intercompany, and reconciliations. Review financial statements, analyze variances, ensure US GAAP compliance, maintain audit-ready controls, and resolve accounting issues. Serve as an accounting subject matter expert while partnering with shared services and cross-functional teams. Drive process simplification, standardization, automation, close-cycle improvements, and financial systems transformation.

Leads six full-stack developers building and maintaining a fintech website while owning GA4, SQL-based analytics, ETL pipelines, dashboards, data quality, and business insights. Sets technical direction, oversees architecture, performance, reliability, and security, partners with Product, UX, and Marketing, manages the website and analytics roadmap, and coaches engineers through hiring, development, and performance management.

Entry-level apprentice supporting data collection, verification, quality assurance, and query resolution across investment and financial datasets. The role includes structured training in investment management, Excel, SQL, and Power BI, collaboration with internal and external stakeholders, and work across rotating shifts in the Mumbai office.