Senior Applied ML Scientist: Personalization & Growth

NerdWallet, Inc

United States

Remote

USD 140,000 - 190,000

Full time

46 hours ago
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Job summary

NerdWallet is looking for a Senior Data Scientist (Applied ML) to join our growing team. You will lead production‑grade machine learning solutions that power customer personalization, predictive modeling, and performance marketing, with a direct impact on how we acquire, engage, and monetize our customer relationships.

You will collaborate with Data Engineering, Product, Marketing, and Analytics to translate complex business problems into scalable ML systems, while helping establish technical

Responsibilities

  • Build Predictive Models That Drive Business Growth
  • Translate model predictions into actionable signals that improve marketing investment decisions, customer acquisition efficiency, and long-term profitability.
  • Advance Personalization Recommendation Systems
  • 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.

Job description

NerdWallet is looking for a Senior Data Scientist (Applied ML) to join our growing team. You will lead production‑grade machine learning solutions that power customer personalization, predictive modeling, and performance marketing, with a direct impact on how we acquire, engage, and monetize our customer relationships.

You will collaborate with Data Engineering, Product, Marketing, and Analytics to translate complex business problems into scalable ML systems, while helping establish technical

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