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Data Scientist III - Financial Crimes Modeling - TD Bank
Data Scientist
Senior data scientist specializing in financial crimes detection, building predictive models and analytics pipelines using Python, SQL, and machine‑learning techniques to uncover fraud patterns and support risk mitigation.
About the role
Key Responsibilities
- Design, develop, and deploy machine‑learning models to detect and prevent financial crime activities such as fraud, money laundering, and illicit transactions.
- Collaborate with fraud analysts, risk managers, and engineering teams to translate business requirements into scalable data solutions.
- Perform exploratory data analysis, feature engineering, and statistical testing on large, heterogeneous datasets.
- Maintain and optimize data pipelines in SQL and Python, ensuring data quality, reproducibility, and real‑time scoring capabilities.
- Communicate model insights and performance metrics through clear visualizations and executive‑level presentations.
Requirements
- Advanced degree (M.S. or Ph.D.) in Computer Science, Statistics, Mathematics, or a related quantitative field.
- 5+ years of professional experience building production‑grade machine‑learning models for fraud or financial crime detection.
- Proficiency in Python (pandas, scikit‑learn, PyTorch/TensorFlow) and strong SQL querying skills.
- Solid foundation in statistical modeling, hypothesis testing, and time‑series analysis.
- Experience with data visualization tools (e.g., Tableau, Power BI, matplotlib) and communicating complex results to non‑technical stakeholders.
Skills
pythonsqlmachine learning