Senior Data Scientist / Analyst, Finance
On-siteNew York City, New York, United States or New York, United States
Job Summary
Build and maintain the financial reporting layer in the data warehouse, modeling tables for close, forecasting, and board reporting. Reconcile general ledger and platform data to ensure clean, accurate financial reports requiring no manual cleanup. Analyze fee structures, incentive returns, and trader retention to drive revenue and retention insights. Partner with finance on monthly close, variance analysis, and investor reporting while replacing ad hoc requests with recurring modeled reports. Write end-to-end documentation to enable team ownership of reports and models. Operate in a fast-moving environment where business logic changes frequently, ensuring high accuracy before publication.
Required Qualifications
- 7+ years in data analysis/science, financial analysis, or a similar role, with production experience building reporting that a finance team depends on
- Expert SQL. You can work through complex joins across transaction-level data without supervision
- Data science background including causal inference, quasi-experimental methods, or predictive modeling in Python or R
- Working knowledge of accounting fundamentals including general ledger structure, accruals, revenue recognition. You're comfortable enough to reconcile a report and recognize when it is wrong
- Experience building in a modern cloud data warehouse such as Databricks, Snowflake, BigQuery, or ClickHouse
- A high bar for accuracy. You reconcile before you publish, and you know which numbers cannot be off by a dollar
- Comfort translating between finance and engineering, where the same word often means two different things
- Comfortable operating in a fast-moving environment where business logic changes frequently and you need to keep pace
Desired Qualifications
- (Plus) Experience with dbt or similar transformation tooling
- (Plus) Familiarity with on-chain data or crypto accounting
- (Plus) Experience in fintech, crypto, prediction markets, or other data-intensive financial products
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