Data Scientist – Financial Crime Risk Management in Toronto

Data Scientist – Financial Crime Risk Management in Toronto

Toronto Full-Time 76800 - 115200 $ / year (est.) On-site
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At a Glance

  • Tasks: Validate cutting-edge financial crime risk models and collaborate with a dynamic team.
  • Company: Join TD, a leading global financial institution committed to innovation.
  • Benefits: Enjoy competitive salary, health benefits, and career development opportunities.
  • Other info: Dynamic work environment with excellent growth potential and supportive culture.
  • Why this job: Make a real impact in financial crime prevention using AI and ML technologies.
  • Qualifications: Post-secondary degree in relevant fields and experience in AML/FCRM modeling.

The predicted salary is between 76800 - 115200 $ per year.

The Model Validation (MV) group in Enterprise Risk, Risk Management is responsible for the independent validation and approval of all analytical models used for TD. The position reports to Senior Manager, Model Validation.

Detailed accountabilities include:

  • Validates Financial Crime Risk Management (FCRM) models including AML, Insider Risk, and Trading Surveillance.
  • Conduct validation testing and analysis for different FCRM models under Senior Manager or Manager supervision to support various business initiatives and regulators requirements.
  • Have effective communication with different stakeholders from 1st line to discuss and solve model limitations/issues identified during the validation process.
  • Deliver high quality model validation reports with adequate information and justification to support validation conclusions and Audit/regulator review/assessment of validation process and validation analysis.
  • Maintains professional knowledge of AI/ML techniques and developments in FCRM modeling.
  • Develops different validation testing tools/programs to assess advanced AI/ML FCRM models.

Education & Experience:

  • Post‑secondary degree in one or more of the following areas: computer science, statistics, mathematics, financial engineering, or engineering.
  • In‑depth knowledge of ML/AI and AI Graph/Network analysis.
  • 2 years + Experience in either developing or validating AML/FCRM model with exposure in AI/ML modelling is an asset.
  • Proficient in relevant programming languages & software such as Python, H2O.AI, Scala, etc.
  • Excellent verbal and written communication skills.
  • Excellent time/project management and multitasking skills with minimal supervision.

Customer Accountabilities:

  • Works in a highly interactive, team‑oriented environment with Big Data developers and analytical experts.
  • Stays current on developments in FCRM modelling.

Shareholder Accountabilities:

  • Works closely with key stakeholders to conduct different validations in time to support different business initiatives.
  • Executes on the validation plan to deliver results aligned with enterprise model validation procedures and model risk policy.

Employee/Team Accountabilities:

  • Shares knowledge, information, skills, and subject matter expertise among the team.
  • Collaborates with other functions and teams to complete validation efficiently and in‑time escalated identified issues.

Data Scientist – Financial Crime Risk Management in Toronto employer: TD

TD Securities is an exceptional employer located in Toronto, Ontario, offering a dynamic work environment that prioritizes innovation and professional growth. With a strong commitment to employee development, competitive compensation, and a comprehensive benefits package, TD fosters a culture of collaboration and inclusivity, empowering colleagues to thrive both personally and professionally. Join a forward-thinking team where your contributions are valued, and you can make a meaningful impact in the capital markets sector.

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Contact Details:

TD Recruitment Team

We think you need these skills to ace Data Scientist – Financial Crime Risk Management in Toronto

Model Validation
Financial Crime Risk Management (FCRM)
Anti-Money Laundering (AML)
Artificial Intelligence (AI)
Machine Learning (ML)
Programming in Python
H2O.AI