Lead Data Scientist - Remote

Discovered MENA; San Francisco (CA); Remote; USD 150,000 - 230,000; Full time

Job summary

A leading data science firm is seeking an Artificial Intelligence & Data Talent Partner to design advanced ML models and enhance transparency through explainability techniques. The role involves collaborating with product and engineering teams to deploy solutions while requiring strong expertise in applied machine learning, quantitative finance, and proficiency in Python and SQL. This full-time, remote position expects candidates to have a background in financial data and blockchain-related analytics.

Qualifications

• 5+ years of experience in applied ML, quantitative finance, or credit-risk modeling.
• Strong Python and SQL skills.
• Experience with ML frameworks like PyTorch, TensorFlow, scikit-learn, or XGBoost.
• Hands-on experience with financial data.
• Familiarity with blockchain and DeFi data.
• Experience deploying ML models into production (APIs, orchestration, or streaming systems).
• Bonus: NLP, vector databases, LLMs / GenAI tools (OpenAI APIs, GPT-4, LangChain, HuggingFace).

Responsibilities

• Design and build hybrid ML models to extract insights from unstructured data.
• Add explainability to models using techniques like SHAP and LIME.
• Build scalable data pipelines and integrate various data sources.
• Develop anomaly detection tools and evaluation frameworks.
• Work closely with Product and Engineering to ship models.
• Backtesting model outputs against historical NAVs, trades, and redemptions.
• Collaborating with Product and Engineering to ship models via APIs, SDKs, and dashboards for traders and risk teams.
• Partnering with CTO on long-term governance, transparency, and AI ethics.

Skills

Applied machine learning

Quantitative finance

Credit-risk modeling

Python

SQL

Machine learning frameworks

Production ML deployment

Data pipelines

API/SDK delivery

NLP/GenAI tools

Tools

PyTorch

TensorFlow

scikit-learn

XGBoost

LangChain

HuggingFace

Job description

Artificial Intelligence & Data Talent Partner at Discovered MENA 🤖

Remote Role

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:

• 5+ years of experience in applied ML, quantitative finance, or credit-risk modeling
• Strong Python and SQL skills, plus experience with ML frameworks like PyTorch, TensorFlow, scikit-learn, or XGBoost
• Solid understanding of time-series forecasting, regression/classification, and probabilistic modeling
• Hands-on experience with financial data (fixed income, private credit, or structured products)
• Familiarity with blockchain and DeFi data, including smart contracts, token metadata, and on-chain events
• Experience deploying ML models into production (APIs, orchestration, or streaming systems)

Bonus to have:

• Background in credit analytics, NAV valuation, or structured credit
• Experience in quant research, fintech data science, or tokenized asset analytics
• Experience with NLP, vector databases, and LLMs / GenAI tools (OpenAI APIs, GPT-4, LangChain, HuggingFace, etc.)

Seniority level

Mid‑Senior level

Employment type

Full‑time

Job function

Science and Information Technology