Data Scientist II: Fraud & Identity Risk Analytics

Uber Eats; Saint-Michel; Presencial; CAD 65.000 - 70.000; Jornada completa

Descripción de la vacante

TD is seeking a Data Scientist II to develop, validate, and optimize internal fraud and authentication models that expand risk capabilities and reduce reliance on external vendor models. You will drive end-to-end development, from data discovery to productionization, while communicating results to both technical and non-technical stakeholders.

You will partner with Strategy, Engineering, Product, Data, Model Validation, and Risk teams to translate business challenges into scalable analytical

Formación

• 3–5+ years of data science, ML, or analytics experience.
• Strong Python and SQL proficiency with ML and visualization.
• Experience building and evaluating predictive models in production.
• Excellent presentation and stakeholder management skills.
• Ability to explain methods and business impact to varied audiences.
• Ability to manage multiple development activities in a fast-paced environment.

Responsabilidades

• Develop, validate, and optimize ML models for fraud detection and risk use cases.
• Lead end-to-end model development lifecycle from data discovery to productionization support.
• Present results to technical and non-technical stakeholders.
• Collaborate with Strategy, Engineering, Product, Data, Model Validation, and Risk teams.
• Prepare documentation for Model Validation and governance.
• Monitor models and identify remediation actions.

Conocimientos

Python

SQL

Machine learning

Statistical analysis

Feature engineering

Data visualization

Educación

Data Science / Statistics / Mathematics / Computer Science / Engineering degree

Herramientas

Azure Databricks

Azure Machine Learning

MLOps pipelines

FICO platforms

Streamlit

Descripción del empleo

TD is seeking a Data Scientist II to develop, validate, and optimize internal fraud and authentication models that expand risk capabilities and reduce reliance on external vendor models. You will drive end-to-end development, from data discovery to productionization, while communicating results to both technical and non-technical stakeholders.

You will partner with Strategy, Engineering, Product, Data, Model Validation, and Risk teams to translate business challenges into scalable analytical