Manager, Data Science & Machine Learning

Lightspeed Commerce; Toronto; Hybrid; CAD 155,000 - 165,000; Full time

Benefits offered by this job

Flexible work environment

Equity options

Pension contributions

Training opportunities

Health and wellness credit

Volunteer time off

Interest groups

Job summary

Lightspeed Commerce in Canada is seeking a Manager, Data Science & Machine Learning to lead a high-performing data science team and deliver production-ready ML solutions across the organization.

The role combines hands-on leadership with strategic enablement, owning the DS/ML model lifecycle from experimentation to production and partnering with MLOps for ongoing maintenance. Strong Python + cloud experience required.

Qualifications

• Hands-on data science experience deploying models to production.
• Experience with ML engineering: serving, monitoring, drift detection, retraining pipelines, and feature stores.
• Familiarity with ML Ops tooling such as MLflow, Vertex AI, Databricks.
• 4+ years of people management experience.
• Proficiency in Python and ability to review code and pipelines.

Responsibilities

• Lead end-to-end DS/ML model lifecycle from experimentation to production.
• Manage day-to-day team priorities, blockers, and delivery standards.
• Define and promote DS/ML best practices, code quality, and documentation.
• Advise other DS teams on methodology and problem solving.
• Collaborate with Data Office leads to align standards and share learnings.
• Partner with MLOps for production releases and model maintenance.

Skills

Data science

Team management

Python

ML engineering

MLOps

Communication

Strategic thinking

Cloud platforms

Tools

MLflow

Vertex AI

Databricks

Job description

Hi there! Thanks for stopping by. Are you actively looking for a new opportunity? Or just checking the market? You might just be in the right place!

We’re looking for a Manager, Data Science & Machine Learning to join our Data team in Canada. The Manager will be a hands‑on leader, responsible for guiding a high‑performing team of data scientists to deliver production‑ready solutions across the organization. This role drives Data Science & Machine Learning model delivery from experimentation to production, owns the Data Science Enablement roadmap while contributing to the overall Data Office plans, and builds the team capabilities needed to scale the practice.

What You’ll Be Doing

Data Science Management & Enablement

• Lead, oversee and own the full lifecycle of Data Science & Machine Learning models from experimentation to production deployment.
• Own day‑to‑day team management, prioritizing work, removing blockers, and ensuring consistent delivery standards.
• Define, document, and champion data science best practices, covering modeling standards, code quality, experimentation frameworks, and documentation.
• Act as subject‑matter authority and internal resource for other data science teams: advising on methodology, reviewing approaches, and helping teams solve complex or ambiguous problems.
• Collaborate with Data Science leads across the business to align on standards, share learnings, and create a cohesive community of practice. Surfacing collaboration opportunities, flagging duplicate work, and brokering knowledge transfer.
• Collaborate with the MLOps team on production release and ongoing maintenance of models.

Team Leadership & People Development

• Set clear expectations and individual performance goals for all direct reports.
• Conduct regular 1:1s, provide timely and actionable feedback, and lead performance calibrations.
• Identify growth opportunities, sponsor stretch assignments, and build individualized development plans.
• Foster a collaborative team culture where experimentation and learning from failure are encouraged, including new AI/ML features or experimental approaches.

Stakeholder Management & Communication

• Participate in project planning and technical brainstorming sessions with business stakeholders and other Data Office leads to translate business problems into technical briefs and communicate results in non‑technical terms.
• Proactively manage expectations, surface risks early, and influence across cross‑functional teams.
• Represent the team’s work in leadership forums, steering committees, and quarterly business reviews.

And a Little Bit Of …

• Contribute as part of the wider team to achieve organizational objectives, even if that means stepping beyond the strict scope of your role.

What You Need To Bring

• 3+ years of hands‑on data science experience, including direct personal deployment of models to production.
• Demonstrated experience with ML engineering practices such as model serving, monitoring, drift detection, retraining pipelines, and/or feature stores.
• Familiarity with modern MLOps tooling (e.g., MLflow, Vertex AI, Databricks).
• 4+ years of experience managing a team of data scientists, including hiring, performance management, and career development.
• Proficiency in Python; comfortable reviewing code, models, and pipeline logic.
• Strong understanding of supervised/unsupervised ML, model evaluation, and common failure modes in production.
• MLOps fluency to collaborate with Senior ML engineers on standards, infrastructure decisions, and technical unblockage.
• Comfort with cloud‑based ML platforms (AWS, GCP, or Azure) and data warehousing environments.
• Strategic thinking: prioritize for impact and help unblock teams.
• Strong communication: translate complex technical work for executive audiences.
• Structured thinking: assess new project ideas across value, feasibility, risk, and strategic fit.
• Proactive identification of dependencies, risks, and blockers before escalation.
• Strong prioritization instincts, thriving in ambiguous environments, and navigating a large volume of competing project ideas.

We know that people are more than what’s on their CV. If you’re unsure you have the right profile for the role, hit the “Apply” button and give it a try!

You’ll Enjoy

• A flexible work environment that empowers you to do your best work.
• A culture that celebrates performance.
• The chance to make an impact in a team that’s big enough for career growth but lean enough for your voice to be heard.
• Career‑defining opportunities.

Benefits

• Flexible paid time off and remote work policies.
• Equity options.
• Contributions to your pension plan.
• Training opportunities.
• Health and wellness credit.
• Time off to volunteer.
• Interest groups, employee‑led networks, and social committees.
• Computer purchase program.
• Enhanced parental leave.

Compensation

The total compensation for this position is expected to be in the range of $155-165K CAD.

Legal & EEO Statements

Please note that we ask applicants to disclose any criminal convictions, and we conduct criminal record checks as part of our hiring process for this role.

At Lightspeed, we carefully consider a wide range of factors when determining compensation, including your skill set, qualifications, experience, and market data. These considerations can cause your compensation to vary.

This is an existing vacancy at Lightspeed. Lightspeed uses artificial intelligence–enabled tools to support certain aspects of the recruitment process; all hiring decisions are made by our recruiting and hiring teams.

Lightspeed does not accept unsolicited agency resumes. If we have not directly engaged your company in writing to supply candidates for a specific vacancy, Lightspeed will not be responsible for any fees related to unsolicited resumes.

Lightspeed is a proud equal opportunity employer and we are committed to creating an inclusive and barrier‑free workplace. Lightspeed welcomes and encourages applications from people with disabilities. Accommodations are available on request for candidates taking part in all aspects of the selection process.

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