Senior ML Data Scientist: Credit Risk & Fraud (Equity)

Zed; San Francisco (CA); On-site; USD 130,000 - 160,000; Full time

Benefits offered by this job

Equity options

Comprehensive benefits package

Flexible working hours

Job summary

Zed, based in San Francisco, is seeking a Senior ML Data Scientist to join their innovative team. In this role, you will work on advanced credit models, leveraging AI to redefine financial services. Ideal candidates will have over 7 years in ML with hands-on experience in deploying state-of-the-art models.

You'll contribute to building robust fraud detection mechanisms and work closely with engineering teams. This is a senior position with significant influence on technical decisions, ideal for those passionate about transforming the banking landscape.

Qualifications

• 7+ years of experience in applied ML or data science focusing on credit risk and fraud.
• Hands-on experience deploying LLMs and transformer architectures in production.
• Proficiency in Python and SQL; knowledge of ML frameworks.

Responsibilities

• Collaborate on credit decisioning and fraud detection models.
• Own data preparation pipelines for modeling inputs.
• Design and deploy fraud detection models in real time.

Skills

Applied ML or data science experience

Hands-on LLM and transformer-based experience

Proficiency in Python and SQL

Strong feature engineering skills

Statistical foundation

Experience building production models

Model-driven vs rule-based approaches

Leadership and communication skills

Tools

XGBoost

LightGBM

PyTorch

Job description

Zed, based in San Francisco, is seeking a Senior ML Data Scientist to join their innovative team. In this role, you will work on advanced credit models, leveraging AI to redefine financial services. Ideal candidates will have over 7 years in ML with hands-on experience in deploying state-of-the-art models.

You'll contribute to building robust fraud detection mechanisms and work closely with engineering teams. This is a senior position with significant influence on technical decisions, ideal for those passionate about transforming the banking landscape.