Senior Data Scientist
Manulife Voir toutes les offres
- Toronto, ON
- Permanent
- Temps-plein
- AI/ML Leadership: Architect, build, deploy, and maintain enterprise-grade AI/ML models in production, ensuring reliability, scalability, and observability.
- Model Operations: Establish best practices for MLOps (CI/CD for ML, monitoring, data/feature pipelines), model governance, and risk controls across large datasets.
- Advanced Analytics: Lead fraud detection solutions leveraging graph analytics; experience with graph databases (e.g., Neo4j) is a plus.
- Cloud Platforms: Drive large-scale data processing and model deployment on Azure (e.g., Databricks, Azure ML), optimizing performance and cost.
- Data Strategy: Oversee complex data exploration, feature engineering, and experiment design to uncover patterns and improve signal quality.
- Innovation: Evaluate and integrate GenAI and emerging methods to enhance detection efficacy and automation.
- Stakeholder Engagement: Translate high-level, ambiguous business problems into clear technical requirements; manage executive and cross-functional stakeholder expectations.
- Communication: Present complex findings in plain English to non-technical audiences; influence decisions with clear narratives and metrics.
- Program Management: Lead multiple concurrent, high-priority projects; plan roadmaps, manage risks, and deliver measurable outcomes.
- Mentorship: Coach and mentor junior data scientists, establishing standards for coding, experimentation, and documentation.
- Global Collaboration: Work across time zones and coordinate with regional teams; flexibility to attend global meetings as needed.
- 5+ years of experience building and maintaining enterprise-grade, large-scale AI/ML models in production environments.
- Advanced degree: Master’s or PhD in Computer Science, Data Science, Statistics, Engineering, or related field.
- Expert-level Python and strong familiarity with PySpark/Spark SQL/Spark ML; rigorous software engineering practices (testing, code review, modular design).
- Proven stakeholder management and the ability to translate complex technical topics for non-technical audiences.
- Demonstrated ability to lead multiple high-priority initiatives and convert vague business asks into clear, actionable technical requirements.
- Experience with Azure Databricks and cloud-native ML tooling; solid understanding of data pipelines and MLOps.
- Track record of mentoring and elevating junior team members.
- Flexibility to collaborate with global teams and attend meetings across time zones.
- Experience in fraud detection or financial crime analytics on a global scale.
- Production experience with graph analytics and graph databases (e.g., Neo4j).
- Hands-on with GenAI (LLMs, retrieval, agentic workflows) for automation and investigation support.
- Experience building production models on datasets with millions+ records; strong performance optimization skills.
- Resilient, outcome-driven, and comfortable operating in dynamic environments.
- We’ll empower you to learn and grow the career you want.
- We’ll recognize and support you in a flexible environment where well-being and inclusion are more than just words.
- As part of our global team, we’ll support you in shaping the future you want to see.