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# Senior Data Scientist - Document Verification

- **Company:** Socure Inc.
- **Location:** San Francisco, CA, United States
- **Experience:** Expert
- **Salary:** $191,000.0 - $230,000.0
- **Contract:** Permanent contract
- **Skills:** A/B Testing, Amazon Web Services, Data Analysis, Computer Vision, Fraud Prevention and Detection, Image Quality, Python (Programming Language), Machine Learning, SQL Databases, Usage Analysis, Apache Spark, Deep Learning, Model Validation, Information Technology, Performance Monitor, Build Tools, GPT, Databricks
- **Published:** August 10, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=299723d453749c45

## About the Role

* 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.

Preferred

 * Experience with computer vision, deep learning, or transformer-based models.
 * Experience designing and analyzing A/B tests, online experiments, and statistical evaluations of product or machine learning performance.
 * Experience defining product KPIs and building dashboards to monitor product performance, customer behavior, and operational metrics.

## Description

We are seeking a highly technical Senior Data Scientist to drive machine learning innovation for Socure's Document Verification (DocV) platform. This role combines model development, product analytics, model evaluation, and ML tooling to improve fraud detection, customer experience, and operational efficiency. You will partner closely with Product, Engineering, Fraud Operations, and Data Science to build production ML models, generate actionable insights, and develop scalable evaluation and automation frameworks., * 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.
 * Design and execute model evaluations using offline and production datasets, measuring precision, recall, FAR/FRR, and business impact.
 * Develop dashboards and KPIs to monitor model health, product performance, and operational metrics.

Tooling & Automation

 * Build tools and automation for model evaluation, performance monitoring, labeling workflows, and fraud investigations.
 * Develop self-service analytics and experimentation frameworks.
 * Improve analytics infrastructure supporting model development and monitoring.


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