Private-Markets Data-Product GCC Design Director

The mandate

Deal screening, diligence and portfolio monitoring rely on spreadsheets and specialist datasets assembled differently by each investment team. The planned Mumbai GCC could industrialise these flows, but leadership has not defined where data-product accountability ends and investment judgment begins. Confidential deal access, valuation assumptions and portfolio-company consent create boundaries that generic enterprise data models do not address.

The four-month deliverable comprises a private-markets data-product charter, three product blueprints and an exercised access-and-lineage pack. Milestone one maps decision use and confidentiality by week three; milestone two fixes product and investment boundaries in month two; milestone three runs deal-leakage, stale valuation and portfolio-restatement scenarios; milestone four delivers launch waves, roles, economics and accepted artefacts.

The client will provide masked deal and portfolio samples, source contracts, valuation calendars, access policies, correction histories and named investment and legal owners. Acceptance requires Mumbai product leads to trace two unseen metrics to authorised source, state use limitations and route a disputed valuation input correctly. Data, investment-operations and legal executives sign each blueprint.

The consultants will not make an investment recommendation, produce a valuation, negotiate data licences, access live restricted deal rooms or implement the production platform. They may define data-product evidence and entitlements but cannot approve a user, adjust a portfolio mark or certify regulatory reporting. Scenario material remains masked and client-controlled.

Outputs include editable product envelopes, confidentiality classes, lineage and correction standards, access decision matrices, role profiles, source-exit gates and economic assumptions. Client teams will adapt the design to a fourth dataset before close to demonstrate usability. Build support after acceptance is separate and cannot restrict the firm’s reuse of methods.

Why this is external work

Investment teams protect differentiated judgment, operations seeks standardisation and legal teams appropriately constrain access, creating no neutral owner for the product design. A conventional data-governance exercise would flatten deal-specific context. Independent private-markets data experience can make repeatable ownership explicit without intruding on valuation or investment authority.

What you will own

• Map deal, portfolio, fund and external data from authorised source through transformation, correction, metric and investment use.
• Define product envelopes for screening intelligence, diligence evidence and portfolio performance with named Mumbai owners.
• Separate data definition, engineering, quality remediation, valuation input, investment interpretation and committee accountability.
• Design confidentiality classes, need-to-know access, deal-code segregation, lineage and correction notification requirements.
• Establish leadership and specialist depth across private-markets domain, data reliability, product and security engineering.
• Exercise unauthorised inference, stale valuation, restated portfolio metric and conflicting source scenarios.
• Deliver three blueprints, access matrix, role architecture, launch economics, transfer gates and unresolved legal choices.

Candidate qualifications

• Designed decision-ready data products for private equity, private credit, infrastructure or another alternative investment portfolio.
• Built an India data capability handling deal confidentiality, portfolio-company restrictions, valuation calendars and source-contract obligations.
• Distinguished data-product ownership from valuation methodology, investment recommendation and accountable investment-committee judgment.
• Recovered lineage or correction failures that changed portfolio monitoring, investor reporting or a live diligence conclusion.
• Designed entitlements and deal-code segregation without preventing reusable engineering, authorised comparison and controlled analysis.
• Delivered operating artefacts that investment professionals and Mumbai product teams independently reused on additional datasets.

Non-negotiables

• Can complete two investment-hub residencies and all four Mumbai milestones within four months.
• Will disclose asset-manager, portfolio-company, data-provider, valuation, fund-administration and technology relationships.
• Brings private-markets data-product and India GCC design; public-market data governance alone is insufficient.
• Accepts masked client records, no investment or valuation authority and joint legal-investment-data acceptance.

1. 49 words maximum. Describe a private-markets data correction that materially changed a portfolio or diligence view.
2. 49 words maximum. Which data-product decision can Mumbai own without determining a valuation assumption?
3. 49 words maximum. What masked source and access evidence must the client provide before week three?