Staff Data Product Manager (Machine Learning) - Canada
NerdWallet is hiring a Staff Data Product Manager (Machine Learning) - Canada for a remote role open to applicants in Canada. It pays CAD 164k-CAD 248k a year and Level rates it ; you can apply on NerdWallet.
Level's read on this job
- Level rates this AI product manager role Builds AI ●●●●: the job is building AI systems.
- This is listed as a remote role.
- The posting mentions Databricks and AI evaluation among its tools and skills.
- NerdWallet has 25 other open roles on Level.
- Posted in the last few days.
AI in this role
NerdWallet’s mission is to provide clarity for all of life’s financial decisions. Machine learning is how we get there at scale. It helps us understand our consumers, personalize their experiences, and connect them with the financial products that fit their needs.
We’re hiring a Staff Data Product Manager to own the ML product roadmap across NerdWallet. You’ll work with our business verticals, Data Scientists, and Engineering teams to find the highest-impact opportunities and take predictive models from idea to production to adoption. The work ranges from customer lifetime value prediction to lead scoring to personalized product recommendations.
This is a product leadership role for someone who is technically fluent in ML. You won’t build models or write production code, but you’ll be a credible, peer-level partner to the people who do. You’ll challenge assumptions on ground truth, evaluation, and serving architecture, and you’ll tie every model to a business outcome.
This role reports to the VP, Data & Analytics.
Where you can make an impact:Partner deeply with Data Science and ML Engineering
Dig into modeling trade-offs, ground-truth definitions, training data quality, precision/recall, and feature strategy alongside Data Scientists and ML Engineers.
Navigate ML infrastructure decisions, including model serving, feature pipelines, batch vs. real-time inference, latency, and production dependencies.
Turn ambiguous business problems into clear model objectives, technical requirements, and measurable success criteria.
Own the roadmap and drive models into production
Own and prioritize the ML roadmap across verticals, balancing business impact, technical feasibility, and engineering capacity. You’ll decide what to build, defer, or say no to.
Work across Data Science, Data Engineering, Product Engineering, and business teams to get model predictions into consumer experiences, real-time decisioning systems, and business workflows.
Make sure every launch is production-ready, with clear ownership of dependencies and validated performance against technical and business requirements.
Measure what matters
Work with Data Science and Analytics on experiments, A/B tests, and causal measurement that prove the incremental impact of ML.
Define and monitor success criteria covering predictive performance, reliability, adoption, and business outcomes.
Explain model performance, trade-offs, limitations, and revenue impact clearly to senior stakeholders.
Lead beyond your own roadmap
Set the long-term vision for ML products, influence without formal authority, and mentor other product managers and partners.
7+ years in Data Product Management, Data Science, Machine Learning, or a related technical field, with a track record of shipping production ML or data products
Deep fluency in applied ML: training data, ground truth, loss functions, precision/recall, overfitting, and model evaluation
Strong understanding of ML platforms and infrastructure: model serving, feature pipelines, batch vs. real-time inference, latency trade-offs, and deployment workflows
Experience partnering directly with Data Scientists and ML Engineers to challenge assumptions and navigate complex dependencies
Experience with modern data and ML tools such as Databricks, Snowflake, AWS, or similar
Strong business sense, with the ability to connect ML work to revenue growth, customer lifetime value, conversion, and marketing efficiency
Excellent communication and cross-functional leadership, including influencing technical and business stakeholders without formal authority
Bachelor’s or advanced degree in Computer Science, Engineering, Statistics, Mathematics, or a related field, or equivalent practical experience
This is a remote position and a person can be located anywhere in Canada (with the exception of Quebec).
NerdWallet is proud to be a remote-first company! We believe great work can be done anywhere. No matter where you are based, NerdWallet offers benefits and perks to support the physical, financial, and emotional well being of you and your family.
Work Hard, Stay Balanced (Life’s a series of balancing acts, eh?)
Monthly Healthcare Stipend
Rejuvenation Policy – Vacation Time Off + You will receive the official public holidays in your province
Paid sabbatical for Nerds to recharge, gain knowledge and pursue their interests
Monthly Wellness Stipend, Wifi Stipend, and Cell Phone Stipend
Work from home equipment stipend
Have Some Fun! (Nerds are fun, too)
Nerd-led group initiatives – Employee Resource Groups for Parents, Diversity, and Inclusion, Women, LGBTQIA, and other communities
Hackathons and team events across all teams and departments
Company-wide events like NerdLove (employee appreciation) and our annual Charity Auction
Plan for your future (And when you retire on your island, remember the little people)
RRSP with a 4% match. Eligible one month after hire.
Financial wellness, guidance, and unlimited access to a Certified Financial Planner (CFP) through Northstar
NerdWallet is committed to pursuing and hiring a diverse workforce and is proud to be an equal opportunity employer. We prohibit discrimination and harassment on the basis of any characteristic protected by applicable federal, state, or local law, so all qualified applicants will receive consideration for employment.
#LI-Remote
#LI-6
How we rate this
Staff Data Product Manager (Machine Learning) - Canada at NerdWallet rates 89 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Also common in AI product manager jobs at this level
Pay
- Typical AI product manager job
- $178k
Use the typical AI product manager figure as a reference when pay comes up. See AI product manager jobs
Questions you could be asked
- How do you decide that one model's output is better than another's for a given task?
- Walk me through how you've used Databricks in your day-to-day work.
- How would you decide a model or AI system is ready to ship?
- Tell me about a time a model underperformed in production. How did you find out, and what did you change?
Adapt your resume
- List these exact terms on your resume: AI Evaluation and Databricks. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.
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