Job Overview
Location
Remote - US
Job Type
Full-time
Category
Data Science
Date Posted
March 24, 2026
Full Job Description
đź“‹ Description
- • As a Data Scientist II specializing in Computer Vision at Socure, you will play a critical role in advancing the company’s mission to build identity trust infrastructure for the digital economy by developing and deploying machine learning models that verify identities in real time and prevent fraud at scale.
- • Your work will directly impact the accuracy, reliability, and performance of Socure’s document verification systems, which are used by businesses, governments, and millions of individuals daily to establish trust in digital interactions.
- • Day to day, you will develop, maintain, and improve machine learning models for document verification use cases including document classification, image quality assessment, field extraction, and fraud detection.
- • You will independently implement and evaluate deep learning architectures such as CNNs and transformer-based vision or multimodal models, ensuring they are robust, scalable, and production-ready.
- • You will own well-defined components of end-to-end ML pipelines, managing data preparation, model training, evaluation, and deployment to production environments with a focus on reproducibility and monitoring.
- • You will conduct in-depth error analysis, model diagnostics, and performance optimization, identifying root causes of failures and proposing data- or model-driven improvements to enhance system accuracy.
- • You will actively contribute to technical design discussions, participate in code reviews, and help establish modeling best practices across the team, fostering a culture of technical excellence and collaboration.
- • You will write production-quality, maintainable Python code and contribute to shared ML tooling and infrastructure, improving efficiency and consistency in model development workflows.
- • You will collaborate closely with engineering and product partners to align model development with product goals, performance benchmarks, and reliability requirements, ensuring seamless integration into Socure’s platform.
- • You will join a high-performing, mission-driven team at Socure that values ownership, critical thinking, and technical rigor, where individuals are empowered to act like owners and solve complex problems with precision.
- • You will have the opportunity to grow your expertise in cutting-edge computer vision and multimodal ML techniques while working on real-world systems that process massive volumes of identity documents with high stakes for accuracy and fairness.
🎯 Requirements
- • Bachelor’s degree in Computer Science, Engineering, Data Science, or a related field, or equivalent experience, with 5+ years of professional experience in machine learning or data science; MS or Ph.D is a plus.
- • Strong proficiency in Python and hands-on experience with ML frameworks such as PyTorch or TensorFlow.
- • Solid experience applying deep learning models, particularly CNNs, in real-world computer vision systems, with working knowledge of transformer-based vision or multimodal approaches.
🏖️ Benefits
- • Opportunity to work on high-impact ML systems that verify identities and prevent fraud for businesses, governments, and millions of users daily.
- • Remote-first work environment within the United States, offering flexibility and autonomy in how and where you work.
- • Collaborative, ownership-driven culture that values technical excellence, innovation, and solving complex problems with precision.
Skills & Technologies
Python
Git
TensorFlow
PyTorch
Data Science
Remote
Degree Required
About Socure Inc.
Socure Inc. provides digital identity verification and fraud prevention software for financial services, fintech, e-commerce and government clients. The platform applies machine learning and graph-based analytics to link and validate identity elements in real time, detecting synthetic identities, account takeover and document fraud. It integrates via APIs and SDKs for onboarding, KYC/AML compliance and transaction monitoring, aiming to reduce false positives and manual reviews while improving approval rates for legitimate users worldwide.
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