As Data Science Team Lead for Risk function, you'll lead a team of 5-7 Data Scientists and Machine Learning Engineers building AI solutions that detect fraud, assess risk, and protect the platform. You'll bridge the gap between complex risk challenges and cutting-edge machine learning, delivering models that operate at scale in production environments.
Key Responsibilities
- Team Leadership: Directly manage and mentor a team of 5-7 data scientists. Foster technical growth, conduct code reviews, and guide the team through complex, ambiguous problems while promoting a culture of experimentation.
- Strategy to Execution: Translate high-level risk management requirements into concrete machine learning problems. Identify high-impact opportunities for AI to improve fraud detection, anomaly scoring, and operational security.
- Hands-on Delivery: Oversee the end-to-end modeling process, including exploratory data analysis (EDA), feature engineering, model selection, and hyperparameter tuning. Ensure the team adheres to best practices in coding, testing, and comparative experimentation.
- Production Focus: Collaborate closely with engineering to deploy models into real-time production systems. Implement robust MLOps practices, including CI/CD pipelines, automated retraining, and continuous performance monitoring to ensure scalability and reliability.
Must-Have Experience
- Management: Proven experience leading Data Science or ML teams.
- Technical Mastery: Expert knowledge of ML/Deep Learning algorithms and Python stack (scikit-learn, TensorFlow/PyTorch, pandas).
- Production Engineering: Track record of deploying models to production with strong MLOps/CI/CD practices.
- Foundations: Strong background in software engineering (OOP) and statistical theory.
- Communication: Fluent English with the ability to explain complex technical concepts clearly.
Nice-to-Have
- Experience with Spark/PySpark and cloud platforms (Azure/Databricks).
- Background in Fraud Detection, Risk, or Cybersecurity.
- Knowledge of real-time scoring and the iGaming/Betting industry