Associate, Data Analytics

About this role The HPS/BlackRock Transaction brings together BlackRock’s corporate and asset owner relationships with HPS’s diversified origination and capital flexibility. BlackRock and HPS have formed a new private financing solutions business unit (“PFS”) led by Scott Kapnick, Scot French, and Michael Patterson, creating an integrated franchise with approximately $370 billion in client assets, including $205 billion of private credit assets. This combined platform, which has more than 590 investment professionals and approximately 1,300 employees globally, offers broad capabilities across senior and junior credit solutions, asset-based finance, real estate, CLOs and GP-LP solutions. As part of the HPS/BlackRock Transaction, Scott Kapnick, Scot French, and Michael Patterson have joined BlackRock’s Global Executive Committee, and Scott Kapnick has been appointed as an observer to the BlackRock Board. About the team The IT Data Analytics team is responsible for sourcing, processing ,distributing data internally and externally. The team covers data needs across all aspects of investment analysis, portfolio management, back -office processing, investor reporting, and regulatory filings. Data Analytics team members collaborate closely with SMEs across Front Office, Backoffice, Investor Relations, Tax, Legal, Management Company in delivering data reporting and analytics technology solutions. PFS is seeking an Associate, IT Data Analytics to join the firm’s technology organization in Mumbai. This role is primarily analytics engineering–focused, with responsibility across data engineering, analytics modeling, business intelligence, and support for AI ‑ enabled analytics use cases supporting HPS’ s Public & Private Credit, CLO, and Long/Short Credit investment platforms. The Associate will work closely with senior analytics engineers, business users, and offshore/onshore development teams to build analytics ‑ ready datasets, dashboards, and reporting solutions used by Portfolio Management, Risk, Operations, Finance, and Investor Relations. Responsibilities Specific responsibilities will include but not be limited to the following: Build and maintain data transformations, curated datasets, and analytics ‑ ready tables used for reporting and analysis. Develop and enhance dashboards and reports using Sigma, Power BI or similar BI platforms. Support semantic modeling, metric definitions, and standardized analytics outputs. Assist with integrating third ‑ party data sources into analytics workflows. Support AI ‑ enabled analytics by preparing high ‑ quality , analytics ‑ ready data inputs. Assist with incorporating AI ‑ driven insights or outputs into dashboards and reporting workflows. Learn and apply best practices around data quality, explainability, and governance for AI use cases. Work with business users to understand reporting needs and translate them into technical requirements. Support ad ‑ hoc analysis and data validation requests. Skills and Qualifications Required 5 years of relevant experience in data analytics, analytics engineering, BI, or data engineering. Strong SQL skills and experience working with analytical datasets. Hands ‑ on experience with BI tools such as Power BI, Tableau, or Qlik. Exposure to cloud data platforms (Azure, Snowflake, or similar) is a plus. Interest or exposure to AI ‑ enabled analytics or advanced analytics is a strong plus. Financial services experience (credit or asset management preferred) is a plus. Strong written and verbal communication abilities and inter-personal skills Highest degree of business ethics and professionalism Ability to perform business analysis, as well as manage and maintain various user relationships Bachelor’s or master’s degree in computer science, Engineering, or related field coupled with an MBA from a tier I (IIT / NIT / BITS / equivalent) or (IIM / ISB / XLRI / equivalent) is preferred. ... (truncated, view full listing at source)