Senior Data Scientist (Applied ML)
About The Position
NerdWallet is seeking a Senior Data Scientist (Applied ML) to help build and advance machine learning capabilities across consumer personalization, predictive modeling, and performance marketing. This hands-on individual contributor role is a foundational position on a new team, with an opportunity to shape team practices and technical standards. The role partners with Data Engineering, Product, Marketing, and Analytics to turn business problems into scalable machine learning solutions. The Senior Data Scientist will lead the development of production-grade machine learning solutions for business decisions, including customer lifetime value prediction, real-time lead scoring, and recommendation engines for matching consumers with financial products. The role uses Databricks and MLflow to develop, train, deploy, monitor, and manage models, and establishes practices for model reliability, reproducibility, and production readiness. It also includes designing experiments to assess business impact and providing technical leadership within Data Science. The role is remote and based in the United States.
Requirements
- At least 5 years of professional experience in Data Science, Applied Machine Learning, or a related field.
- Demonstrated track record of developing and deploying machine learning solutions that drive measurable business impact.
- Deep, hands-on experience with Databricks, including production machine learning workflows using MLflow and the Databricks ML ecosystem; experience with similar platforms is not a substitute.
- Advanced proficiency in Python and SQL.
- Extensive experience with modern machine learning frameworks such as scikit-learn, XGBoost, LightGBM, PyTorch, or TensorFlow.
- Strong understanding of supervised learning, predictive modeling, classification, regression, ranking, and model evaluation techniques.
- Practical experience designing scalable batch and/or real-time inference systems, with an understanding of latency, reliability, and performance trade-offs.
- Strong software engineering fundamentals, including version control, testing, modular code design, and CI/CD practices for machine learning.
- Ability to independently lead complex, ambiguous technical initiatives from problem definition through deployment and business impact measurement.
- Strong business acumen and ability to connect technical solutions to measurable outcomes such as revenue growth, conversion improvement, customer lifetime value, and marketing efficiency.
- Excellent communication and collaboration skills, including experience influencing technical direction and working with senior stakeholders and cross-functional teams.
- Bachelor’s or advanced degree in Computer Science, Statistics, Mathematics, Engineering, or a related quantitative discipline, or equivalent practical experience.
Responsibilities
- Lead end-to-end development of machine learning models for customer lifetime value, 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.
- Develop recommendation and ranking models to identify relevant financial products for consumers based on their needs, behaviors, and predicted propensity to engage or convert.
- Explore and implement propensity modeling, learning-to-rank, and next-best-product recommendation approaches.
- Collaborate with Product and Marketing to integrate predictive intelligence into consumer experiences and personalized communications.
- Use Databricks and MLflow to develop, train, deploy, monitor, and manage machine learning models at scale.
- Establish data science practices for experiment tracking, model versioning, feature engineering, automated training pipelines, model monitoring, and reproducibility.
- Define standards for model performance, reliability, retraining, and production readiness, including monitoring for data drift and model degradation.
- Design and evaluate experiments to measure deployed models’ incremental business impact and improve their effectiveness.
- Mentor other practitioners, influence architectural decisions, and elevate engineering and modeling standards across the organization.
- Lead complex technical initiatives from problem definition through deployment and measurement of business impact.
- Work with cross-functional teams and senior stakeholders to connect technical solutions to measurable business outcomes.
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 5 years.
- Health and Dependent Care FSA and HSA plans with monthly NerdWallet contributions.
- Monthly wellness, cell phone, and (for eligible remote employees) Wi-Fi stipends.
- Work-from-home equipment stipend and co-working space subsidy for eligible remote employees.
- Employee Resource Groups and team events.
- Eight hours of volunteer time off per quarter and a company match for charitable donations.
- 401(k) with a 4% company match.
- Access to new financial products and tools.
- Financial wellness guidance and unlimited access to a Certified Financial Planner through Northstar.
- Employer-paid disability and life insurance premiums.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
