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Role Description

We're looking for a Senior Data Scientist with deep computer vision and ML expertise to join our document verification team. You'll own ML systems that analyze identity documents at scale — from model design through production — while also serving as a trusted technical advisor to customers. This role blends hands-on engineering with real customer impact.

• Design, build, and own deep learning models — including CNNs and transformer-based vision and multimodal architectures — for document classification, fraud detection, image quality assessment, field extraction, and authenticity checks.
• Own ML solutions end to end: data analysis, model training, deployment, monitoring, and continuous improvement in production.
• Lead technical deep dives with customers, explaining model behavior, performance metrics, and tradeoffs in ways that are clear and actionable.
• Translate customer, regulatory, and business requirements into modeling objectives, and communicate results effectively to both technical and non-technical audiences.
• Partner with engineering and product teams to deliver scalable, reliable document verification systems.

Qualifications

• 8+ years of hands-on experience in computer vision, or a Bachelor's in Computer Science (or related field) with equivalent professional depth.
• Proven track record designing, building, and maintaining production ML systems.
• Strong written and verbal communication skills, including experience in customer-facing technical roles.
• The ability to translate technical details into business-facing narratives — not just the "what," but the "why."
• Comfort balancing technical rigor with customer, business, and compliance needs.

Requirements

• Master's or Ph.D. in Computer Science, Machine Learning, Computer Vision, or a related field.
• Experience with document verification, OCR, identity, fraud detection, or image forensics.
• Familiarity with transformer-based vision models, multimodal systems, or LLMs.
• Experience working with enterprise customers or in regulated environments.