ML Scientist — Personalization & Product Recommendations

credible; United States; On-site; 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

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.