Data Scientist

credible; United States; Remote; USD 89,000 - 136,000; Full time

Benefits offered by this job

Annual discretionary bonus

Medical, dental, vision insurance

401(k) plan

Paid time off

Job summary

credible is seeking a data science leader to expand ML capabilities in a consumer finance marketplace. You will own end-to-end modeling projects from exploration to production, influencing long-term ML strategy for recommendations, user classification, personalization, and retargeting.

Responsibilities include guiding vision with cross-functional teams, conducting EDA, evaluating feasibility, and monitoring model performance. Strong cloud and MLOps experience are essential.

Qualifications

• Bachelor's degree in Mathematics, Statistics, Computer Science or a related quantitative field.
• 3+ years of experience developing, testing, and deploying predictive models for in-product use.
• Advanced statistical modeling in Python or R, plus strong SQL, data mining, and data cleansing.

Responsibilities

• Drive the long-term ML vision, partnering with product, marketing, and engineering teams.
• Perform exploratory data analysis and feasibility assessments for ML solutions.
• Monitor and diagnose model performance, drift, and new use cases.
• Design, prototype, and implement models across domains from data prep to prod deployment.
• Improve product recommendations and user classification for adaptive experiences.

Skills

Python

R

SQL

Data mining

Data cleansing

ML deployment

GitHub

Cloud experience

Neural networks

Decision trees

Education

Bachelor's degree in Mathematics, Statistics, Computer Science

Master's degree strongly preferred

Tools

AWS EC2

S3

Redshift

Snowflake

Container environments

Seldon Core

ML deployment tooling

Job description

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.