Lead Data Scientist / ML Engineer - Remote Role

Job description

What you’ll be working on :

• Designing and building hybrid ML models that combine supervised learning, time‑series forecasting, and NLP to extract insights from unstructured data like PDFs, fund memos, and regulatory filings.
• Adding explainability to models using techniques like SHAP, LIME, and feature attribution so outputs are transparent and human‑readable.
• Building scalable data pipelines across off‑chain fundamentals, on‑chain activity, and macro benchmarks.
• Integrating data from sources like FRED, PitchBook LCD, Securitize, Centrifuge, Maple, and TrueFi, with strong data lineage and freshness guarantees.
• Developing anomaly detection and reconciliation tools across issuer, administrator, and blockchain datasets.
• Creating evaluation frameworks to measure accuracy, confidence intervals, latency, and data quality.
• Backtesting model outputs against historical NAVs, secondary‑market trades, and redemptions.
• Researching and incorporating credit‑risk signals (CDS spreads, recovery rates, default data, etc.).
• Building continuous learning loops using live market data and partner feedback.
• Working closely with Product and Engineering to ship models via APIs, SDKs, and dashboards used by traders, curators, and risk teams.
• Collaborating with data providers, protocol teams, and fund administrators to improve coverage and signal quality.
• Partnering with the CTO on long‑term model governance, transparency, and AI ethics.

What I’m looking for :

Bonus to have :

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