Staff Data Scientist

About the Role

The role reports to the VP, Data & Analytics, and is part of a team that values scientific rigor, technical expertise, and collaboration. As a senior data scientist, you will be expected to set the standard for technical excellence, mentor junior team members, and provide technical leadership across the organization.

NerdWallet is committed to creating a culture that is inclusive, flexible, and candid, where employees are empowered to grow, take smart risks, and be themselves. The company offers a range of benefits and perks, including remote work options, professional development opportunities, and a comprehensive compensation package.

What You Will Do

• Lead the design and implementation of causal inference frameworks to measure true incremental impact across personalization, marketing, and lifecycle interventions
• Establish and standardize methodologies for incrementality, experimentation, and measurement across channels and product surfaces
• Build and scale LTV models for real-time decisioning, including churn-adjusted and horizon-specific approaches
• Develop and deploy personalization models that influence ranking, offer selection, content sequencing, and monetization strategies
• Ship production-grade machine learning models that directly drive revenue outcomes, including marketplace optimization, partner routing, and budget allocation
• Translate predictive outputs into decision-ready signals for real-time systems
• Partner with Data Engineering and Platform teams to define data instrumentation, feature stores, and model monitoring frameworks
• Influence architectural decisions across modern data and ML platforms
• Provide technical leadership across teams by setting best practices for experimentation, modeling, code quality, and reproducibility
• Mentor and develop senior and mid-level data scientists to raise the overall technical bar across the organization
• Communicate complex analytical insights and trade-offs to executive stakeholders and translate findings into actionable business strategies

What We Are Looking For

• 8+ years of experience in applied machine learning, causal inference, experimentation, or related quantitative fields
• Deep expertise in causal inference methodologies, including uplift modeling, doubly robust learners, instrumental variables, difference-in-differences, synthetic control, and Bayesian time series
• Proven experience building and operationalizing LTV models for real-time or near-real-time applications
• Strong software engineering and production ML experience, including Python, pandas, numpy, scikit-learn, LightGBM/XGBoost, and PySpark
• Advanced SQL skills and experience with distributed systems and modern data platforms
• Strong technical leadership and communication skills, with the ability to set technical direction and mentor junior team members
• Experience working with cross-functional teams, including Product, Engineering, Marketing, and Finance
• Bachelor's or Master's degree in a quantitative field, such as computer science, statistics, or mathematics

Nice to Have

• Experience with cloud-based data platforms, such as Snowflake or Databricks
• Knowledge of real-time inference systems and model serving platforms
• Familiarity with DevOps practices and tools, such as Docker, Kubernetes, or Jenkins
• Experience with agile development methodologies and version control systems, such as Git
• Certification in data science or machine learning, such as Certified Data Scientist or Certified Machine Learning Engineer

Benefits and Perks

• Competitive salary and bonus structure
• Comprehensive health, dental, and vision insurance
• 401(k) matching and retirement savings plan
• Flexible PTO and remote work options
• Professional development opportunities, including conference sponsorships and training programs
• Access to cutting-edge technologies and tools, including machine learning frameworks and data platforms
• Collaborative and dynamic work environment with a team of experienced data scientists and engineers
• Opportunities for career growth and advancement, including leadership roles and technical specialist positions
• Comprehensive benefits package, including disability insurance, life insurance, and employee assistance programs
• Remote stipend and home office setup support
• Access to mental health resources and employee wellness programs
• Recognition and reward programs, including employee of the month and year awards
• Social events and team-building activities, including happy hours, game nights, and volunteer opportunities

• Highlight your expertise in causal inference and machine learning: Make sure your resume and cover letter demonstrate your experience with causal inference methodologies, such as uplift modeling and instrumental variables, and machine learning frameworks, such as scikit-learn and PySpark.
• Showcase your technical skills: Emphasize your proficiency in programming languages, such as Python and SQL, and data platforms, such as Snowflake and Databricks.
• Demonstrate your ability to communicate complex technical concepts: Provide examples of how you have effectively communicated technical ideas to non-technical stakeholders, such as product managers and executives.
• Be prepared to discuss your experience with cross-functional teams: Talk about your experience working with product, engineering, marketing, and finance teams to drive business outcomes.
• Research the company culture and values: Show your passion for NerdWallet's mission and values, and be prepared to discuss how you can contribute to the company's culture and community.
• Prepare to back up your claims with examples: Use specific examples from your experience to demonstrate your technical expertise, leadership skills, and ability to drive business outcomes.
• Don't be afraid to ask questions: Prepare a list of questions to ask the interviewer about the role, the team, and the company culture.