Data Scientist

Role overview

This role expands the data science and machine learning capability within a consumer finance marketplace that helps millions of people compare financial products. The position leads end-to-end ownership of modeling projects, from exploratory analysis through production deployment, while influencing the long-term ML strategy across product recommendations, user classification, personalization, and retargeting.

Responsibilities

• Drive the long-term statistical modeling and machine learning vision for the business, partnering with product, marketing, and engineering teams.
• Perform exploratory data analysis before model development and run feasibility assessments or proof-of-concepts for proposed ML solutions.
• Monitor and diagnose model performance, including drift, degradation, and new use case opportunities.
• Design, prototype, and implement models across multiple domains, managing the full lifecycle from data preparation to production deployment.
• Improve product recommendation and user classification systems to power adaptive experiences, cross-sell initiatives, and retargeting efforts.
• Convert insights about users into automated services in collaboration with product, marketing, and engineering counterparts.

Requirements

• Bachelor's degree in Mathematics, Statistics, Computer Science, or a related quantitative field; a master's degree in a quantitative or scientific discipline is strongly preferred.
• 3 or more years of experience developing, testing, and deploying optimized predictive models, ideally to support in-product recommendations or automated retargeting.
• Advanced statistical modeling skills in Python, R, or comparable tools, plus strong SQL, data mining, and data cleansing capabilities.
• Deep knowledge of supervised and unsupervised machine learning algorithms, including neural networks and decision trees.
• Hands-on experience with cloud infrastructure such as AWS EC2, S3, Redshift, Snowflake, and container-based environments.
• Familiarity with experiment design, version control using GitHub, and ML deployment infrastructure such as Seldon Core or similar MLOps tooling.
• Demonstrated use of AI tools to accelerate day-to-day data science workflows.
• Excellent written and verbal communication, including the ability to explain complex analyses in clear business terms.

Nice to have

• Prior experience at an e-commerce or fintech company.

Benefits and work setup

• Pay range of approximately $102,000 to $136,000 USD in high cost-of-labor markets such as New York City and San Francisco, and $89,000 to $124,000 USD in other US locations, with final offer dependent on education, skills, experience, and location.
• Eligibility for an annual discretionary bonus.
• Benefits package includes medical, dental, and vision insurance, a 401(k) plan, paid time off, and other offerings subject to plan documents.