Head of Fund Analytics & Automation — Credit Fund
RemoteUnited States
Job Summary
Design and run the full deal workflow from origination intake through the credit committee, implementing governed automation with LLM-assisted steps and complete audit trails for LP due diligence. Build the ingestion and storage layer for borrower financials and Xsolla transaction telemetry using PostgreSQL, ETL pipelines, and materialized views, then develop credit scoring models in Python with rigorous train/test discipline and ongoing drift monitoring. Operate investor and borrower dashboards that reconcile to source systems, manage AI-assisted automation costs, and enforce strict data protection policies. Present numbers and automation stacks directly to investors and borrowers, field diligence questions, and evolve into an operating role overseeing portfolio monitoring and covenant tracking as the fund goes live.
Required Qualifications
- 7+ years across data analytics / data engineering, including recent hands-on experience building and running production automation (not prototypes or notebooks)
- Proven production experience with LLM-based automation: schema-validated outputs, human review gates, evaluation and regression testing, cost-tiered model routing
- Strong SQL and Python; ownership of a PostgreSQL (or similar) data platform end to end — ETL, materialized views, performance tuning, data contracts
- Workflow orchestration experience (n8n, Airflow, or comparable)
- BI and dashboarding: Tableau, Power BI, Qlik, or equivalent web dashboards; a track record of reporting that executives actually used for decisions
- Security discipline for sensitive data: role-based access, deny-by-default policies, audit trails, PII handling
- Finance background: degree in finance or quantitative field plus real experience in portfolio analytics, market risk, or credit — able to hold their own in an underwriting or investor conversation
- Strong written and spoken English; comfortable presenting to senior external audiences
Desired Qualifications
- Direct exposure to private credit, lending, or fund operations
- Forecasting and statistical modeling track record (capacity planning, SLA/risk forecasting, or similar)
- Experience with embeddings / semantic search and multi-model AI setups
- Web development ability (React / TypeScript or similar) for internal tools and dashboards
- Experience in audited or regulated environments (SOC 2, fund audits, or equivalent)
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