Lead Data Scientist - Big Data and Modelling

AI overview

Lead the design and deployment of machine learning models for risk scoring and fraud detection while managing a team of data scientists and engineers.

Lead the design, development, and deployment of machine learning models for risk scoring, fraud detection, and behavioural analytics
Drive feature engineering, model training, and model monitoring pipelines using large-scale datasets
Build and maintain a scalable data infrastructure in collaboration with the Data Engineering team
Manage and mentor a team of data scientists and engineers, ensuring high standards in model accuracy, interpretability, and governance
Translate complex business problems into data-driven solutions and communicate technical insights clearly to stakeholders
Lead model validation, backtesting, and performance analysis for new and existing models
Develop and implement data quality checks, pipelines, and data governance protocols

Bachelor’s or Master’s in Data Science, Computer Science, Applied Mathematics, or related field
3+ years of experience in data science, machine learning, or risk modeling, ideally in fintech or banking
Strong command of Python, SQL, and big data tools (e.g., Spark, Airflow, Hadoop, AWS/GCP/Databricks)
Experience leading end-to-end model development in production environments
Solid understanding of credit risk, fraud analytics, or financial modelling