Senior Manager, Data Science

Vancity • Vancouver, BC

63d • Hybrid

About The Position

We are building an Applied Machine Learning (ML) & Decision AI Pod and are seeking a Senior Manager, Data Science to lead the development and delivery of classic machine learning and decision intelligence solutions - including forecasting, predictive models, experimentation, and production scoring, statistical and mathematical analysis.

This role is a hands-on technical leader and people manager who will work closely with Data Scientists, ML Engineers, Analytics partners, and Cloud Engineers to take models from problem framing → Proof of Concept → production. You may also partner with vendors to accelerate delivery, ensure solutions meet internal standards, and integrate vendor-built capabilities into our platforms.

This is a Full-time, Permanent role and will report directly to the Director, AI Centre of Excellence. Our head office is based in Vancouver, but we are open to candidates in BC and Ontario. While this position is for an existing vacancy and provides a hybrid work arrangement, you will be expected to be on-site for events and business demands when needed.

Requirements

• 8–12 years of experience in Data Science, Applied ML, Analytics Engineering, ML Engineering, or related fields
• Bachelor’s or Master’s degree (PhD preferred) in Computer Science, Engineering, Mathematics or a related field
• 2+ years of people leadership (or strong team lead experience with hiring, coaching, and delivery ownership)
• Proven experience delivering classic ML in production environments, including forecasting and/or predictive scoring models
• Strong expertise in MLOps / ML deployment architecture, including CI/CD, model lifecycle management, monitoring, and operational readiness
• Hands-on cloud experience with Azure, and fluency deploying ML workloads in Azure (e.g., Azure ML, Azure DevOps patterns, identity/security basics)
• Ability to work effectively with vendors, including oversight of technical delivery, validation, and integration
• Strong applied ML foundations (model selection, evaluation design, feature engineering, calibration, time series fundamentals for forecasting)
• Comfort working with structured data and collaborating on data engineering practices required for robust modeling
• Practical understanding of production ML: drift, monitoring, retraining strategies, interpretability, and governance requirements
• Strong communication skills and the ability to influence cross-functionally

Nice To Haves

• Familiarity with other cloud ecosystems such as AWS or GCP (Vertex AI)
• Domain experience in credit risk, fraud detection, or member personalization using ML / data science algorithms
• Experience with Databricks (for ML workflows, feature engineering, orchestration, and/or MLflow)
• Strong mathematical background (statistics, optimization, time series)
• Experience integrating ML outputs into decision engines, automation/RPA workflows, or downstream operational systems
• Exposure to Responsible AI and model risk governance practices

Responsibilities

• Lead end-to-end delivery of classic ML solutions, including forecasting, predictive modeling, and scoring used to drive business decisions and automation
• Own key components of the ML lifecycle: problem framing, feature engineering, model development, evaluation, validation, deployment, and ongoing performance monitoring
• Drive experimentation and iteration using measurable outcomes (lift, accuracy, calibration, stability, fairness, and operational KPIs)
• Translate business needs into analytical approaches and decision logic that can be scaled across teams
• Lead the design and implementation of MLOps architecture, collaborating with Integration, CI/CD, platform teams, and vendors to operationalize models from PoC to production
• Define standard patterns for:  Model packaging, versioning, approvals, and release management CI/CD for ML (build/test/deploy), automated validation, and gated promotion Monitoring for drift, data quality, performance decay, and retraining triggers
• Ensure solutions are designed for reliability, security, cost efficiency, and auditability in Azure and Databricks ecosystems
• Establish reusable templates and reference pipelines for batch and (where needed) real-time scoring
• Partner with external vendors to deliver forecasting or ML capabilities, ensuring alignment with internal architecture, security, and engineering standards
• Validate vendor deliverables (methodology, metrics, documentation, model artifacts), and ensure successful integration into Azure ML / Databricks
• Drive knowledge transfer so internal teams can maintain and evolve solutions after delivery
• Lead and develop a pod working across Data Scientists, ML Engineers, Analytics, and Cloud Engineers
• Set clear priorities, delivery rhythms (agile ceremonies), technical direction, and quality standards
• Mentor team members in applied ML best practices and production readiness
• Collaborate with the Intelligent RPA Pod and GenAI Pod to integrate predictive scoring and decision intelligence into broader automation workflows
• Partner with managers, senior managers, and business stakeholders to prioritize the Applied ML roadmap
• Communicate trade-offs clearly (speed vs. robustness, cost vs. accuracy, build vs. buy, batch vs. real-time)
• Present recommendations with strong narrative and evidence, suitable for both technical and non-technical audiences

Benefits

• Living Wage Employer: We’re the largest private-sector Living Wage Employer in Canada and consistently ranked among Canada’s Top Employers.
• Customizable Benefits: Permanent employees receive flexible benefit packages that can be tailored annually to meet evolving needs.
• Generous Vacation: New employees start with 3-4 weeks of vacation per year, with additional days earned over time.
• Extra Stat Holidays: In addition to BC’s 11 statutory holidays, we offer 2 extra days, plus care days for personal or family illness.
• Immediate Health Coverage: Health and dental benefits begin on your hire date, with three levels of coverage to choose from.
• Defined Benefit Pension: Our retirement plan provides a guaranteed income for life, recognizing that retirement looks different for everyone.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level