Staff Data Product Manager (Machine Learning)
About The Position
NerdWallet is hiring a Staff Data Product Manager to own the machine learning product roadmap across the company. The role works with business verticals, Data Scientists, and Engineering teams to identify high-impact opportunities and move predictive models from concept through production and adoption. Example applications include customer lifetime value prediction, lead scoring, and personalized product recommendations. This is a product leadership role requiring technical fluency in machine learning. The manager will not build models or write production code, but will partner credibly with the teams that do, challenge assumptions about ground truth, evaluation, and serving architecture, and connect each model to a business outcome. The position reports to the VP, Data & Analytics and is remote within the U.S. The role includes setting the long-term vision for ML products, prioritizing work across business verticals, ensuring production readiness, measuring technical and business performance, explaining trade-offs and impact to senior stakeholders, and influencing and mentoring partners without formal authority.
Requirements
- 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, including training data, ground truth, loss functions, precision and recall, overfitting, and model evaluation.
- Strong understanding of ML platforms and infrastructure, including model serving, feature pipelines, batch versus 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 and 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.
Responsibilities
- Partner with Data Scientists and ML Engineers on modeling trade-offs, ground-truth definitions, training data quality, precision and recall, and feature strategy.
- Navigate ML infrastructure decisions, including model serving, feature pipelines, batch versus real-time inference, latency, and production dependencies.
- Translate ambiguous business problems into model objectives, technical requirements, and measurable success criteria.
- Own and prioritize the ML roadmap across business verticals, balancing business impact, technical feasibility, and engineering capacity; decide what to build, defer, or decline.
- Coordinate across Data Science, Data Engineering, Product Engineering, and business teams to integrate model predictions into consumer experiences, real-time decisioning systems, and business workflows.
- Ensure launches are production-ready, dependencies have clear ownership, and performance is validated against technical and business requirements.
- Work with Data Science and Analytics on experiments, A/B tests, and causal measurement to demonstrate ML’s incremental impact.
- Define and monitor success criteria covering predictive performance, reliability, adoption, and business outcomes.
- 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 other product managers and partners.
Benefits
- Medical, dental, and vision health care plans for employees and dependents.
- Flexible vacation time off, 11 holidays, and a holiday company shutdown.
- New parent leave for employees with a newborn child or a child placed with them for adoption or foster care.
- Mental health support.
- Paid sabbatical after five years.
- Health and Dependent Care FSA and HSA plans with a monthly NerdWallet contribution.
- Monthly wellness, cell phone, and Wi-Fi stipends; Wi-Fi stipend is available to remote employees.
- Work-from-home equipment stipend and coworking space subsidy for remote employees.
- Employee Resource Groups and team events, including hackathons.
- Eight hours of volunteer time off per quarter and company matching for charitable donations.
- 401(k) with a 4% company match.
- Early access to test and benefit from new financial products and tools.
- Financial wellness guidance and unlimited access to a Certified Financial Planner through Northstar.
- Disability and life insurance with employer-paid premiums.
Stand Out From the Crowd
Upload your resume and get instant feedback on how well it matches this job.
What This Job Offers
Job Type
Full-time
Career Level
Senior
