This is a hands-on individual contributor role for someone with deep expertise in applied machine learning, production ML systems, and the Databricks ecosystem. As a foundational member of the team, you’ll partner closely with Data Engineering, Product, Marketing, and Analytics to translate complex business problems into scalable ML solutions, while helping establish the technical standards and best practices for machine learning across NerdWallet.

Where you can make an impact:

Build Predictive Models That Drive Business Growth

Lead the end-to-end development of advanced machine learning models focused on customer lifetime value (LTV), conversion propensity, lead quality, and revenue optimization.

Translate model predictions into actionable signals that improve marketing investment decisions, customer acquisition efficiency, and long-term profitability.

Advance Personalization & Recommendation Systems

Develop recommendation and ranking models that identify the most relevant financial products for individual consumers based on their needs, behaviors, and predicted propensity to engage or convert.

Explore and implement approaches such as propensity modeling, learning-to-rank, and next-best-product recommendations to improve customer engagement and cross-sell opportunities.

Collaborate with Product and Marketing to integrate predictive intelligence into consumer experiences and personalized communications.

Establish Best-in-Class ML Practices

Leverage Databricks and MLflow to develop, train, deploy, monitor, and manage machine learning models at scale.

Establish robust DS practices, including experiment tracking, model versioning, feature engineering, automated training pipelines, model monitoring, and reproducibility.

Senior Data Scientist (Applied ML)

Responsibilities

Benefits

Company

Nerdwallet

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