Senior Fraud ML Scientist - Production-Ready Impact

Aimlroles; Northern (KY); Hybrid; USD 135,000 - 165,000; Full time

Benefits offered by this job

Competitive salary

Medical, dental & vision benefits

Stock options

Generous PTO

401(k) with Morgan Stanley

Job summary

Extend is seeking a Senior ML Data Scientist to own the development of fraud-detection models using signals from hundreds of millions of users. You will drive end-to-end ML lifecycle from requirements through monitoring, partnering with product, engineering, and Fraud Intelligence to translate messy data into scalable production systems.

You’ll work to stop bad actors, improve risk assessment, and unlock business value in a high-impact role within the Fraud & Machine Learning team.

Qualifications

• Bachelor’s degree in Mathematics, Statistics, CS, Engineering, OR Operations Research or similar.
• 3+ years of production ML experience building and deploying models.
• Strong proficiency in Python and SQL; solid ML fundamentals.

Responsibilities

• Own the model lifecycle: requirements, experimentation, development, evaluation, and model cards; collaborate on deployment.
• Translate fraud patterns into ML solutions and define success metrics.
• Design and maintain feature engineering pipelines for model development.
• Monitor model quality in production, detect data drift, and retrain when needed.
• Partner with leadership, GTM, fraud operations, product, and engineering to define fraud strategies.
• Champion continuous learning, experimentation, and collaboration across teams.

Skills

Python

SQL

PyTorch

scikit-learn

XGBoost

Fraud detection

Data analysis

Model deployment

Team collaboration

Attention to detail

Education

Bachelor's degree in a quantitative field

Tools

AWS SageMaker

PyTorch Geometric

Arize

Graph data analysis

Job description

Extend is seeking a Senior ML Data Scientist to own the development of fraud-detection models using signals from hundreds of millions of users. You will drive end-to-end ML lifecycle from requirements through monitoring, partnering with product, engineering, and Fraud Intelligence to translate messy data into scalable production systems.

You’ll work to stop bad actors, improve risk assessment, and unlock business value in a high-impact role within the Fraud & Machine Learning team.