Manager, Data Science & Machine Learning
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Key skills for this role
About the Role
Lightspeed Commerce is looking for a Manager, Data Science & Machine Learning to lead a team of data scientists in delivering production-ready solutions. The role involves managing the full lifecycle of ML models, defining best practices, and collaborating with stakeholders.
Key Skills for This Role
Responsibilities
- Lead, oversee and own the full lifecycle of Data Science & Machine Learning models from experimentation to production deployment
- Own the day to day management of the team, ensuring prioritization, unblocking, and delivery standards
- Define, document, and champion data science best practices covering modeling standards, code quality, experimentation frameworks, and documentation
- Serve as a subject matter authority and internal resource for other data science teams
- Collaborate with Data Science leads to align on standards, share learnings, and create a cohesive community of practice
- Collaborate with the 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 and actionable feedback, and lead performance calibrations
- Identify growth opportunities, sponsor stretch assignments, and build individualized development plans
- Participate in project planning and technical brainstorming sessions with business stakeholders
Requirements
- 3+ years of hands on data science experience with deploying models to production
- Demonstrated experience with ML engineering practices including 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 directly managing a team of data scientists, including hiring, performance management, and career development
- 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, strong communication, structured thinking, ability to prioritize
Full Job Posting
Role Overview
- We’re looking for a Manager, Data Science & Machine Learning to join our Data team in Canada. The Manager, Data Science & Machine Learning is a hands on leader, responsible for guiding a high performing team of data scientists to deliver impactful, production ready solutions across the organization.
What You’ll Be Doing
- Lead, oversee and own, as needed, the full lifecycle of Data Science & Machine Learning models from experimentation to production deployment.
- Own the day to day management of the team by ensuring the right work is being prioritized, the team is unblocked, and delivery standards are consistently met.
- Define, document, and champion data science best practices: covering modeling standards, code quality, experimentation frameworks, and documentation.
- Serve as a 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 in other parts of the business to align on standards, share learnings, and create a cohesive data science community of practice.
- Collaborate with the MLOps team on the production release and ongoing maintenance of their models.
- 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.
- Participate in project planning and technical brainstorming sessions with business stakeholders and other Data Office leads.
What You Need To Bring
- 3+ years of hands on data science experience, with direct personal experience deploying models to production (not just experimentation or prototyping).
- Demonstrated experience with ML engineering practices that include 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 with directly managing a team of data scientists, including hiring, performance management, and career development.
- 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 in defining standards, reviewing infrastructure decisions, and unblocking technical challenges.
- Comfort with cloud based ML platforms (AWS, GCP, or Azure) and data warehousing environments.
- Strategic thinking, strong communication, structured thinking, ability to prioritize.
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 to make your voice heard
- 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
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