Our Story & Purpose:
We’re Vancity, a member-owned credit union built on the principles of inclusion and social justice. Since 1946, our relentless commitment to these values has helped us challenge the status quo and break down barriers. We’ve made bold commitments to become net-zero by 2040 across all mortgages and loans, and we’re actively pursuing strategies in Indigenous banking and financial resilience for our members.
We are committed to being a pioneer in Ethical AI. We design and deploy AI systems responsibly—grounded in fairness, transparency, privacy, and human-centered values—to ensure technology benefits our members, communities, and society at large.
As the largest private sector Living Wage Employer in Canada, we’re proud to be consistently recognized as one of the country’s Top Employers. If you’re ready to join our team of 2,300 diverse individuals, access competitive rewards and benefits, and be part of a greater movement - apply today!
Your Role in Supporting Our Members:
We are building an Applied Machine Learning (ML) & Decision AI Pod and are seeking a Senior Manager or 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.
How You'll Make an Impact:
Applied ML & Decision AI Delivery (Classic ML Ownership)
- 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
MLOps & Production Architecture (Azure ML + Databricks)
- 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
Vendor Partnership & Delivery Governance
- 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
People Leadership & Cross-Functional Collaboration
- 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
Stakeholder Management & Communication
- 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
What You’ll Bring to the Team:
- 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
Extra Skills That Set You Apart:
- 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
You’ll Thrive Here If You Are:
- A Hands-On Delivery Leader:You like to coach teams while staying close to the work—helping shape experiments, reviewing modeling approaches, and ensuring models are production-ready, monitored, and maintainable.
- Technically Fluent in Production ML:You understand what it takes to operate models reliably in the real world and can lead MLOps architecture across Azure ML and Databricks, collaborating with Integration and CI/CD partners to make deployment repeatable.
- Collaborative & Communicative:You can align stakeholders, manage vendors, and translate complex ML trade-offs into clear, actionable decisions that drive outcomes.
We value lived experience, so if you are interested in this role, we encourage you to apply even if you feel your skills don't perfectly align with those listed.
What You’ll Earn:
This role offers a salary range of $141,100 to $174,300 per annum. The base pay offered may vary depending on factors such as relevant qualifications, skills, previous experience, and internal equity. As part of our total rewards package, employees may also be eligible for our annual incentive program, subject to program eligibility requirements.
Why You’ll Love Working Here:
A career at Vancity is more than just a job, you’re joining a tradition of change-makers who are creating lasting change for our communities. Beyond base pay, we offer a comprehensive total rewards package to ensure our employees are empowered to thrive:
- 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.
Vancity Talent Programs:
Vancity supports an inclusive hiring process for candidates who self-identify as Indigenous, Black, or Trans. With special permission from the BC Human Rights Commissioner, this initiative provides access to career development opportunities, prioritized job screening, and feedback. Any information you choose to share will be stored securely and used only for recruitment and career development connected to this initiative, in line with the BC Personal Information Protection Act (PIPA). For details, please see our dedicated Talent Programs job posting.
This role is an open vacancy, and our hiring process is grounded in fairness, transparency, and inclusion. We are committed to an inclusive, barrier-free and accessible recruitment experience for all candidates. If you require any accommodations or support at any stage of the recruitment process (including the application stage), we encourage you to let us know by contacting our Talent Acquisition team at [email protected]. We’re here to work with you to ensure your needs are met promptly and effectively. All requests will be handled with the utmost respect and confidentiality, so you can participate fully in the process.
