Data Scientist developing machine - learning models for The Athletic’s sports media platform. Optimizing subscriptions, workflows, experiments, and personalized article recommendations.
About the role
- Data Scientist developing network-based financial-crime detection for TD Bank. Building models, visualizations, and decision-support tools to prioritize high-risk customer connections.
Responsibilities
- Translate financial crime typologies into detection strategies and develop querying logic
- Generate hypotheses, design analytical approaches, and validate findings through data analysis
- Perform exploratory data analysis to identify emerging risk patterns, customer characteristics, and risk operation insights
- Synthesize and present data-driven findings and recommendations to technical and non-technical audiences
- Design and develop interactive visualization and decision-support tools for business users
- Automate recurring operational workflows
- Develop, calibrate, and test supervised-learning models for network ranking
- Monitor model performance and evaluate modelling methodologies
- Develop new detection methodologies and analytical approaches
- Translate business problems into structured analytical problems and practical solutions
- Conduct root-cause and impact analyses
- Independently review and challenge existing methodologies and analytical solutions
- Assess assumptions, data, results, and business implications and recommend enhancements
- Contribute to documentation, governance, controls, and ongoing monitoring
- Collaborate with internal team members, business users, data engineers, technology teams, and other partners
Requirements
- Bachelor's degree in STEM (e.g., Science, Technology, Engineering, Mathematics, Statistics, Data Science, Economics)
- 1 year or above of work experience; intern/co-op experience in analytical fields counts
- SQL
- Python for data analytics
- Statistics
- ML/AI modelling experience is a bonus
- Large Language Modelling experience is a bonus
- AI agentic experience is a bonus
- Anti-financial crime domain knowledge is beneficial but not required
- Regulatory and governance knowledge and working experience are beneficial but not required
Benefits
- Base salary
- Variable compensation
- Health and well-being benefits
- Savings and retirement programs
- Paid time off
- Banking benefits and discounts
- Career development support
- Regular development conversations, training programs, and online learning platform
- Mentoring programs
- Reward and recognition programs
- Training and onboarding sessions
- Accessibility accommodations throughout the interview process
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