Manager, Data Science & Machine Learning
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Key skills for this role
About the Role
Lightspeed Commerce is seeking a hands-on Manager, Data Science & Machine Learning to lead a high-performing team of data scientists. The role involves driving ML model delivery from experimentation to production, owning the Data Science Enablement roadmap, and building team capabilities.
Key Skills for This Role
Responsibilities
- Lead the full lifecycle of Data Science & Machine Learning models from experimentation to production deployment
- Manage day to day team operations, prioritize work, unblock team, and ensure delivery standards
- Define and champion data science best practices including modeling standards, code quality, and documentation
- Collaborate with MLOps team on production release and maintenance of models
- Set performance goals, conduct 1:1s, provide feedback, and lead performance calibrations
- Participate in project planning and technical brainstorming with business stakeholders
- Represent team's work in leadership forums, steering committees, and quarterly business reviews
Requirements
- 3+ years of hands on data science experience with production model deployment
- 4+ years of experience directly managing a team of data scientists
- Proficiency in Python
- Strong understanding of supervised/unsupervised ML and model evaluation
- Familiarity with MLOps tooling (e.g., MLflow, Vertex AI, Databricks)
- Comfort with cloud based ML platforms (AWS, GCP, or Azure)
- Strategic thinking and strong communication skills
Full Job Posting
Overview
- We're looking for a Manager, Data Science & Machine Learning to join our Data team in Canada.
- This is a hands on leader responsible for guiding a high performing team of data scientists to deliver impactful, production ready solutions.
What You'll Be Doing
- Lead, oversee and own the full lifecycle of Data Science & Machine Learning models from experimentation to production deployment.
- Own day to day management of the team: prioritize work, unblock team, ensure delivery standards.
- Define, document, and champion data science best practices: modeling standards, code quality, experimentation frameworks, documentation.
- Serve as subject matter authority for other data science teams; advise on methodology and review approaches.
- Collaborate with Data Science leads across business to align standards and share learnings.
- Collaborate with MLOps team on production release and ongoing maintenance of models.
- Set clear expectations and individual performance goals for direct reports.
- Conduct regular 1:1s, provide timely feedback, lead performance calibrations.
- Identify growth opportunities and build individualized development plans.
- Participate in project planning and technical brainstorming with business stakeholders.
- Proactively manage expectations, surface risks early, influence cross functional teams.
- Represent team's work in leadership forums, steering committees, and quarterly business reviews.
What You Need To Bring
- 3+ years of hands on data science experience with production model deployment.
- Demonstrated experience with ML engineering practices: model serving, monitoring, drift detection, retraining pipelines, feature stores.
- Familiarity with modern MLOps tooling (e.g., MLflow, Vertex AI, Databricks).
- 4+ years of experience directly managing a team of data scientists.
- Proficiency in Python; comfortable reading and 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.
- Comfort with cloud based ML platforms (AWS, GCP, or Azure) and data warehousing environments.
- Strategic thinking: zoom out to prioritize for impact, zoom in to help unblock.
- Strong communication: translate complex technical work for executive audiences.
- Structured thinking: rapidly assess new project ideas across value, feasibility, risk, strategic fit.
- Ability to proactively identify dependencies, risks, and blockers.
You'll Enjoy
- Flexible work environment that empowers you to do your best work.
- A culture that celebrates performance.
- Career defining opportunities.
- Flexible paid time off and remote work policies.
- Equity options.
- Contributions to your pension plan.
- Training opportunities to grow your skills and career.
- Health and wellness credit.
- Time off to volunteer.
- Enhanced parental leave.
Compensation
- Total compensation expected in the range of CAD 155 165K CAD.
- Benefits include medical, dental, wellness, life and disability insurance, RRSP plan and match, paid parental leave top up, and paid time off.
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