Senior machine learning engineer building recommendation and personalization systems for Pinterest’s creative discovery platform. Improving ML models across Homefeed, Ads, Growth, Shopping, and Search.
About the role
- Staff Data Product Manager owning NerdWallet’s machine-learning roadmap. Connecting predictive models to personalized financial products, consumer experiences, and business outcomes.
Responsibilities
- Own the ML product roadmap across NerdWallet
- Partner with business verticals, Data Scientists, and Engineering teams to identify high-impact opportunities
- Take predictive models from idea through production and adoption
- Evaluate modeling trade-offs, ground-truth definitions, training data quality, precision/recall, and feature strategy
- Navigate ML infrastructure decisions including model serving, feature pipelines, batch vs. real-time inference, latency, and production dependencies
- Translate ambiguous business problems into model objectives, technical requirements, and measurable success criteria
- Prioritize the ML roadmap across verticals based on business impact, technical feasibility, and engineering capacity
- Work across Data Science, Data Engineering, Product Engineering, and business teams to integrate predictions into consumer experiences, real-time decisioning systems, and business workflows
- Ensure launches are production-ready with clear dependency ownership and validated performance
- Collaborate on experiments, A/B tests, and causal measurement
- Define and monitor predictive, reliability, adoption, and business-outcome success criteria
- Explain model performance, trade-offs, limitations, and revenue impact to senior stakeholders
- Set the long-term vision for ML products, influence without formal authority, and mentor product managers and partners
- Report to the VP, Data & Analytics
Requirements
- 7+ years in Data Product Management, Data Science, Machine Learning, or a related technical field
- 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
- Experience with Databricks, Snowflake, AWS, or similar
- Strong business sense connecting ML work to revenue growth, customer lifetime value, conversion, and marketing efficiency
- Excellent communication and cross-functional leadership
- Bachelor’s or advanced degree in Computer Science, Engineering, Statistics, Mathematics, or a related field, or equivalent practical experience
- Must be located in Canada, except Quebec
Benefits
- Monthly Healthcare Stipend
- Rejuvenation Policy – Vacation Time Off
- Official public holidays in your province
- Paid sabbatical
- Monthly Wellness Stipend
- Wifi Stipend
- Cell Phone Stipend
- Work from home equipment stipend
- Employee Resource Groups
- Hackathons and team events
- Company-wide events
- RRSP with a 4% match, eligible one month after hire
- Financial wellness guidance
- Unlimited access to a Certified Financial Planner (CFP) through Northstar
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