Senior Manager- AI/ML Science

Who we are:

Founded in 1998 at Vancouver, lululemon is a performance and lifestyle product company that create transformational products and experiences that build meaningful connections, unlocking greater possibility and wellbeing for all. We are driven by our brand purpose to elevate human potential by making individuals feel their best which helps us design our products with high filter and high style. We use a unique product creation methodology called Science of Feel in all our products to offer convenient, comfortable, and long-lasting experience. We owe our success to our innovative products, commitment to our people, and the incredible connections we make in every community we're in.

About this team:

The Enterprise Data & AI organization is a strategic and operational driver of growth for lululemon, owning and building the data and AI platforms and services that enable the enterprise to operate with intelligence at scale. The team leads the design and delivery of a trusted unified data foundation, AI-driven data analytics and insights, and AI solutions across lululemon's vertically integrated retail ecosystem, while embedding strong data governance and responsible AI practices from the very beginning. By applying AI to critical business challenges and creating new, transformative AI solutions, the team helps reshape how lululemon operates. Through deep partnership with product, technology, and business teams, Enterprise Data & AI accelerates product innovation, unlocks measurable value, elevates guest and educator experiences, and drives enterprise efficiency

Core responsibilities:

As a Senior Manager, AI/ML Science, you lead a team of Applied AI/ML Scientists, setting scientific direction, building delivery capability, and ensuring your team produces rigorous AI/ML solutions that drive measurable business value. You lead a team of scientists who are deep in the inner workings of AI/ML — with the expertise to modify and adapt models, improve performance by making changes to model architecture, and design new algorithms to solve problems. You establish AI/ML science best practices spanning method selection, solution design, experimentation, and responsible AI, manage performance, coach team members on scientific craft and business problem-solving, and create an environment that fosters innovation and rigorous evaluation. You maintain strong technical credibility, partner closely with AI/ML engineering, data engineering, product, and business stakeholders, and ensure AI/ML science work is delivered with statistical rigor and translates effectively into production impact.

• Own the development and delivery of the team's AI/ML science work from business problem framing through validated solutions ready for production — designing operating rhythms, sequencing experimentation and model development workstreams, managing dependencies, and making execution trade-offs that keep programs on track
• Set scientific direction for the AI/ML science capability area — translating business problems into solution approaches, making algorithm and modelling choices within scope (existing models vs. new), model architecture and adaptation), and leading work that goes beyond applying existing models to modifying, adapting, or designing new algorithms and model architectures to achieve desired performance on specific problems
• Contribute hands-on to critical scientific work including solution design, methodology selection, model development, and evaluation on the team's most complex and ambiguous problems — demonstrating best practices, unblocking the team, and maintaining technical credibility
• Establish AI/ML science standards for the team — including experimentation protocols, evaluation rigour, bias and fairness testing, responsible AI assessment, and model documentation — building the expectation that scientists own the integrity of their solutions end-to-end
• Manage complex stakeholder relationships across the capability area - influencing without authority, aligning competing priorities across technology and business partners, and building the cross-functional trust that enables delivery at scale

Qualifications:

• Bachelor's degree in Computer Science, Data Science, Information Technology, or related field, or equivalent experience
• 13 - 16 years of experience
• Make methodological and architectural decisions for the team's AI/ML solutions spanning modelling approach, evaluation design, and integration with downstream systems, balancing scientific rigour with business constraints
• Prioritize AI/ML scientific investments within the team's scope, weighing applied research directions, experimentation infrastructure, and emerging method adoption against expected business value
• Establish the team's AI/ML solution design and evaluation systems — experimentation protocols, evaluation criteria, responsible AI assessment, and model documentation — to enable rigorous and repeatable scientific delivery

Must haves:

• Acknowledge the presence of choice in every moment and take personal responsibility for your life.
• Possess an entrepreneurial spirit and continuously innovate to achieve great results.
• Communicate with honesty and kindness and create the space for others to do the same.
• Lead with courage, knowing the possibility of greatness is bigger than the fear of failure.
• Foster connection by putting people first and building trusting relationships.