Data Science and Machine Learning Manager

The Data Science and Machine Learning Manager is responsible for guiding a highly performing team of data scientists to deliver impactful and production-ready solutions at scale across the organization. In this role, you will oversee the delivery of data science and machine learning (DS/ML) models, from experimentation to production deployment. You will also be responsible for planning the data science enablement roadmap, contributing to the global data office roadmaps, and strengthening the team's capabilities to scale this practice.

Data Science Management and Enablement

• Lead, supervise, and take ownership of the full lifecycle of DS/ML models, from experimentation to production deployment.
• Manage the team's daily operations, ensuring work prioritization, obstacle removal, and consistent delivery standards.
• Define, document, and promote best practices in data science: modeling standards, code quality, experimentation frameworks, and documentation.
• Serve as a subject matter expert and internal resource for other data science teams: advise on methodologies, review approaches, and assist in solving complex or ambiguous problems.
• Collaborate with data science leaders from other business sectors to align standards, share learnings, and create a cohesive practice community. Additionally, identify collaboration opportunities, flag duplicate work, and facilitate knowledge transfer within the organization.
• Partner with the MLOps team for production deployment and ongoing model maintenance.

Team Leadership and Talent Development

• Establish clear performance expectations and individual goals for all team members under your direct responsibility.
• Conduct regular one-on-one meetings, provide constructive feedback, and guide performance evaluations.
• Identify growth opportunities, propose challenging stretch assignments, and build individualized development plans.
• Foster a collaborative team culture where experimentation and learning from failure are encouraged, including for AI/ML or other experimental approaches.

Stakeholder Management and Communication

• Participate in project planning and brainstorming sessions with business partners and other Data Office leaders as an expert, helping to translate business problems into technical requirements and communicate results in simple, non-technical terms.
• Manage stakeholder expectations proactively, raise risks quickly, and influence cross-functional teams.
• Present and advocate for the team's work at executive forums, steering committees, and quarterly business reviews.

And a little extra...

• Contribute to organizational objectives within the broader team, even when it involves tasks outside your defined role.
• Required Experience

The ideal candidate has personally deployed production-scale models, managed teams throughout the data science lifecycle, possesses excellent prioritization instincts, thrives in ambiguous environments, and can navigate a high volume of competing project ideas to focus the team on high-value work.

• More than 3 years of hands-on data science experience, with direct personal experience in deploying models to production (not just experimentation or prototyping).
• Demonstrated experience with ML engineering practices, including model serving, monitoring, drift detection, retraining pipelines, and/or feature stores. You don't need to be an engineer, but you must be able to manage them credibly.
• Strong knowledge of modern MLOps tools (e.g., MLflow, Vertex AI, Databricks).
• More than 4 years of direct experience managing a data science team, including recruitment, performance management, and career development.
• Proficiency in Python; ability to read and review code, models, and pipeline logic.
• Solid understanding of supervised and unsupervised learning (ML), model evaluation, and common failure modes in production.
• Familiarity with MLOps concepts to collaborate effectively with senior ML engineers in defining standards, reviewing infrastructure decisions, and solving technical challenges.
• Comfort with cloud-based ML platforms (AWS, GCP, or Azure) and data warehouse environments.
• Strategic thinking: ability to step back to prioritize based on impact, then dive into details to help unblock situations.
• Excellent communicator: ability to translate complex technical concepts for executive audiences without oversimplifying.
• Structured mindset: ability to quickly evaluate a new project idea based on value, feasibility, risk, and strategic fit.
• Proactive: ability to identify dependencies, risks, and obstacles before they become emergencies or escalations.
• Embrace the Change:
• You'll enjoy:
• A flexible work environment that allows you to perform at your best
• A culture that celebrates performance
• The opportunity to have an impact within a team large enough to grow professionally but agile enough for your voice to be heard
• Opportunities that will shape your career
• Don't forget benefits designed to support your happiness, health, and well-being:
• Flexible paid time off and remote work policies
• Employee stock options, because it's also your company
• Contributions to your retirement plan, because your future matters to us
• Opportunities for training to develop your skills and career
• Health and wellness allowance to feel at your peak
• Volunteer leave and community engagement opportunities
• Interest groups, from employee-led groups to sponsored sports teams
• Computer purchase program to acquire your personal MacBook
• Enhanced parental leave to support growing families

Drive your growth. Find your team.

At Lightspeed, your growth is our priority. We invest in you through continuous learning opportunities, international mobility, and benefits designed to support you, all within a motivated, diverse, and inclusive team passionate about the success of our communities.

Please note that we ask candidates to disclose any criminal conviction and that we conduct a background check as part of our hiring process for this position.

Lightspeed is proud to be an equal opportunity employer and is committed to creating an inclusive and barrier-free workplace.

Lightspeed welcomes and encourages applications from individuals with disabilities. Accommodations are available upon request for candidates who participate in all aspects of the selection process.

About Us

Powering the retail businesses that drive the global economy, Lightspeed's all-in-one commerce platform helps retailers innovate to simplify, adapt, and deliver exceptional customer experiences. Our cloud-based solution transforms and unifies online and offline operations, omnichannel sales, expansion with new locations, international payments, financial solutions, and supplier network connections.

Founded in Montreal, Canada, in 2005, Lightspeed is listed on both the New York Stock Exchange (NYSE: LSPD) and the Toronto Stock Exchange (TSX: LSPD). With teams in North America, Europe, and the Asia-Pacific region, the company serves businesses in the retail, restaurant, and hospitality sectors.