Senior Data Scientist – Document Verification & Fraud AI

United States Digital Space LLC; San Francisco (CA); Hybrid; USD 150,000 - 210,000; Full time

Job summary

United States Digital Space LLC is seeking a highly technical Senior Data Scientist to drive ML innovation for the Document Verification platform. You will develop production models, partner with product and engineering, and push for precision and scale.

The role focuses on model evaluation, fraud detection insights, and building analytics tooling. You will own end-to-end ML workflows, run experiments, and communicate findings to steer product decisions.

Qualifications

• MS/PhD (or equivalent experience) in Computer Science, Statistics, Data Science, or a related field.
• 5+ years of experience in machine learning, data science, fraud analytics, or product analytics.
• Strong experience developing and evaluating production ML models.
• Expert SQL and Python skills.
• Experience with Databricks, Spark, AWS Sagemaker, or similar platforms.
• Strong understanding of experimentation, statistical analysis, and ML evaluation.

Responsibilities

• Design, develop, and improve ML models for document verification, fraud detection, image quality assessment, biometric verification, and related use cases.
• Research new features, modeling approaches, and fraud detection techniques to improve production performance.
• Partner with Engineering to deploy, monitor, and continuously improve production models.
• Analyze product performance, fraud trends, customer behavior, and emerging attack vectors.

Skills

SQL

Python

Databricks

Spark

AWS

MLOps

Education

MS/PhD in Computer Science/Statistics/Data Science

Tools

Databricks

Spark

AWS Sagemaker

Job description

United States Digital Space LLC is seeking a highly technical Senior Data Scientist to drive ML innovation for the Document Verification platform. You will develop production models, partner with product and engineering, and push for precision and scale.

The role focuses on model evaluation, fraud detection insights, and building analytics tooling. You will own end-to-end ML workflows, run experiments, and communicate findings to steer product decisions.