# Head of Data Science - Document Verification & Biometrics

**Company:** [Socure](https://hotfix.jobs/companies/socure)
**Location:** New York, NY, San Francisco, CA, Seattle, WA, Washington, DC, Miami, FL
**Role:** Engineering Management
**Salary:** $250k – $300k/yr
**Experience:** 10+ years
**Skills:** Computer Vision, Multimodal Ai, Vision-Language Models, Foundation Models, PyTorch, Python, Deepfake Detection, Biometrics, Liveness Detection, Agentic Systems, Vector Databases, Embeddings, Adversarial Attacks
**Posted:** 2026-05-08

> Leads data science strategy for AI-powered document verification, biometrics, and reusable identity systems. Drives foundation models, agentic architectures, and fraud detection while managing a team of scientists. Requires 10+ years experience, MS/PhD, and deep expertise in computer vision and multimodal AI.

## Job Description

## What You'll Do

- Own and define the data science vision for Document Verification, Biometrics, and Reusable ID, delivering step-function improvements in accuracy, speed, and user experience.
- Lead and scale a high-performing team of data scientists and applied researchers, setting a high standard for execution, innovation, and accountability.
- Architect and deploy state-of-the-art **computer vision** and **multimodal systems**, including **vision-language models (VLMs)**, for document understanding, face matching, liveness detection, and identity verification.
- Drive the development of domain-specific **foundation models** tailored to identity, documents, and biometrics, leveraging large-scale proprietary datasets.
- Lead the transition to **agentic systems**, building intelligent agents that can reason over document and biometric signals, automate verification workflows, and adapt dynamically to new fraud patterns.
- Advance fraud and attack detection capabilities, including **deepfake detection**, **presentation attack detection**, and **counterfeit document detection**.
- Design and implement secure and robust systems resilient to emerging threats such as **prompt injection** and **adversarial attacks** on multimodal and agent-based systems.
- Leverage **vector databases** and **embedding systems** to power similarity search, identity linking, and reusable identity experiences.
- Partner closely with Product, Engineering, and Risk teams to deliver scalable, production-grade solutions that meet both business and regulatory requirements.
- Drive rapid experimentation and deployment, balancing innovation with reliability, explainability, and compliance.
- Own customer communication and stakeholder management, serving as a trusted technical leader in engagements with customers, partners, and internal stakeholders.
- Represent Socure externally as a thought leader in biometrics, document AI, and fraud prevention.

## What You Bring

- Advanced degree (**MS/PhD** preferred) in Computer Science, Electrical Engineering, Machine Learning, or a related field.
- **10+ years** of experience in data science, machine learning, or applied AI, with a strong track record of building and deploying production systems.
- Deep expertise in **computer vision** and **multimodal AI**, including experience with **vision-language models (VLMs)**.
- Proven experience building domain-specific **foundation models** or large-scale representation learning systems.
- Strong understanding of **biometric systems**, including face recognition, liveness detection, and anti-spoofing techniques.
- Experience detecting and mitigating **deepfakes**, **presentation attacks**, and **counterfeit documents**.
- Strong understanding of **agentic system design**, including agent skills, orchestration/harness frameworks, and real-world deployment of autonomous or human-in-the-loop agents.
- Experience with **vector databases** and **embedding-based retrieval systems**.
- Strong awareness of emerging attack vectors, including **prompt injection**, **adversarial inputs**, and model exploitation techniques.
- Proven ability to lead and scale high-performing teams while delivering under ambiguity and tight timelines.
- Proficiency in **Python** and modern ML frameworks (e.g., **PyTorch**).
- Proven ability to engage with customers and external stakeholders, clearly explaining complex AI systems, trade-offs, and outcomes to both technical and non-technical audiences.

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