Data Scientist
Core
Drive the ML/DL research agenda for a client-classification engine and transaction risk control/anti-fraud scenarios across the trading chain, owning the end-to-end experiment loop from hypothesis to monitored rollout.
Role type
Senior IC machine-learning engineer (risk & fraud)
Builds
Client classification engine, transaction risk control, and anti-fraud systems for trading platforms
Domain
Fintech, financial services, trading infrastructure
Deliverable
production ML models
Required skills
Python, SQL, scikit-learn, PyTorch, TensorFlow, experiment design, backtesting, validation, time-series modeling, deep learning (LSTM, GRU, Transformers), representation learning, handling imperfect data, distributed compute (Spark/Databricks)
Preferred skills
fraud/anomaly detection, user behavior modeling, reputation/risk scoring, cloud analytics stacks, large-scale experimentation
Responsibilities
Turn business questions into measurable data solutions; explore and apply ML/DL models for integrity and classification problems; design fair evaluation strategies and conduct robust backtesting; partner with engineers to ship and monitor models; report findings to technical and business stakeholders
Seniority
Senior, hands-on IC