LightSpeed Retail

Manager, Data Science & Machine Learning

LightSpeed Retail$155K — $165K *
Information Technology
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • 3+ years of hands-on data science experience with model deployment in production
  • 4+ years of experience managing a team of data scientists
  • Experience with ML engineering practices: model serving, monitoring, and retraining pipelines
  • Familiarity with modern MLOps tools like MLflow and Databricks
  • Proficiency in Python for code and model review
  • Strong communication skills for translating technical information
  • Comfort with cloud-based ML platforms (AWS, GCP, Azure)

Responsibilities

  • Lead the full lifecycle of Data Science & Machine Learning models from experimentation to production
  • Manage the daily activities of the team, prioritizing work and ensuring delivery standards
  • Define and implement data science best practices and documentation
  • Serve as a subject matter expert and advisor for data science teams
  • Collaborate with other Data Science leads on standards and knowledge transfer
  • Work with the MLOps team on model production release and maintenance
  • Participate in project planning sessions and translate business problems into technical briefs

Benefits

  • Flexible paid time off and remote work policies
  • Equity options for employees
  • Contributions to pension plans
  • Training opportunities for career development
  • Health and wellness credits
  • Time off for community volunteering
  • Employee-led networks and social committees
  • Computer purchase program for personal devices
  • Enhanced parental leave benefits
Full Job Description
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. This role is responsible for driving Data Science & Machine Learning model delivery from experimentation through production, owning the Data Science Enablement roadmap planning while contributing to the Data Office's org roadmaps, and building the team capabilities needed to scale the practice.

What you'll be doing:

Data Science Management & Enablement
  • 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. Additionally, surfacing opportunities for collaboration, flagging where work is being duplicated, and brokering knowledge transfer across the organization.
  • Collaborate with the MLOps team on the production release and ongoing maintenance of their 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. This includes new AI/ML features or other experimental approaches.

Stakeholder Management & Communication
  • Participate in project planning and technical brainstorming sessions with business stakeholders and other Data Office leads as an expert to help design and translate business problems into technical briefs and communicating 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....
  • Contributing as part of the wider team to achieve organizational objectives even if this means doing things that aren't strictly within the scope of your role.

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. You don't need to be an engineer, but you need to manage them credibly.
  • 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, you can zoom out to prioritize for impact, then zoom in to help unblock.
  • Strong communication, you can translate complex technical work for executive audiences without over-simplifying.
  • Structured thinking, you can rapidly assess a new project idea across value, feasibility, risk, and strategic fit
  • Ability to proactively identify dependencies, risks, and blockers before they become escalations
  • Strong prioritization instincts, ability to thrive in ambiguous environments, and navigate a large volume of competing project ideas to focus the team on the highest-value work

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

Be a changemaker

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

Plus benefits designed to keep you happy, healthy and fulfilled.
  • Flexible paid time off and remote work policies
  • Equity options, because this is your company too
  • Contributions to your pension plan. Your future matters
  • Training opportunities to grow your skills and career
  • Health and wellness credit so you feel your best
  • Time off to volunteer and give back to your community
  • Interest groups, employee led networks, social committees to sponsored sports teams
  • Computer purchase program to get your personal Macbook
  • Enhanced parental leave to support growing families

Fuel your growth. Find your people.

At Lightspeed, your growth is our priority. We invest in you with continuous learning opportunities, global mobility and benefits designed to support you-all within a driven, diverse and inclusive team that's passionate about empowering our communities.

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. We reasonably expect the total compensation for this position to be in the range of $155-165K CAD. Lightspeed also provides a variety of employee benefits including, but not limited to, medical, dental, wellness, life and disability insurance, RRSP plan and match, paid parental leave top-up, and paid time off.

Please note that this compensation information is solely for candidates hired to perform work within Ontario and reflects the amount Lightspeed is willing to pay at the time of this posting. This role represents 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.

To all recruitment agencies: 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.

Where to from here?

Obviously, this has to be mutually beneficial: we want you to step into a role you love, and we want to offer you a place you're proud to come to every day. For a glimpse into our world check out our career page here.

About LightSpeed Retail

LightSpeed Retail is a cloud-based point-of-sale and e-commerce software provider for retailers and restaurateurs. The company was founded in 2005 by Dax Dasilva and is headquartered in Montreal, Canada. LightSpeed Retail's platform allows businesses to manage their inventory, process transactions, and analyze sales data. The company's mission is to help businesses grow by providing them with the tools they need to succeed. LightSpeed Retail has raised over $290 million in funding from investors such as Caisse de dépôt et placement du Québec, iNovia Capital, and Accel Partners.
Learn more about LightSpeed Retail
Size
1,000 employees
Market Cap
$18.4 billion
Industry
Founded
2005
5 Year Trend
+48.5%

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