Job description

WHY SOCURE? Socure is building the identity trust infrastructure for the digital economy — verifying 100% of good identities in real time and stopping fraud before it starts. The mission is big, the problems are complex, and the impact is felt by businesses, governments, and millions of people every day. We hire people who want that level of responsibility. People who move fast, think critically, act like owners, and care deeply about solving customer problems with precision. If you want predictability or narrow scope, this won’t be your place. If you want to help build the future of identity with a team that holds a high bar for itself — keep reading. SENIOR DATA SCIENTIST – DOCUMENT VERIFICATION Summary 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. RESPONSIBILITIES MACHINE LEARNING & MODEL DEVELOPMENT - 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. ANALYTICS & MODEL EVALUATION - 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. CROSS-FUNCTIONAL COLLABORATION - Partner with Product, Engineering, Fraud Operations, and Solutions Engineering to translate business needs into data-driven solutions. - Communicate technical findings and influence product and modeling decisions. QUALIFICATIONS REQUIRED - 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. Socure is an equal opportunity employer that values diversity in all its forms within our company. We do not discriminate based on race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. If you need an accommodation during any stage of the application or hiring process—including interview or onboarding support—please reach out to your Socure recruiting partner directly. Follow Us! YouTube youtube.com | LinkedIn linkedin.com | X (Twitter) x.com | Facebook facebook.com

Requirements

Must-haves

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.
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.
Partner with Product, Engineering, Fraud Operations, and Solutions Engineering to translate business needs into data-driven solutions.
Communicate technical findings and influence product and modeling decisions.
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.

Nice-to-haves

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.
If you need an accommodation during any stage of the application or hiring process—including interview or onboarding support—please reach out to your Socure recruiting partner directly.

Application prep

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Keywords to mirror

machine learningmlsqlpythonaws

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