Data Scientist (Face Biometrics)

Daon Inc

8h•Remote

About The Position

As part of a collaborative team of research and data scientists based in Europe, you will play a meaningful role in advancing Daon's biometric solutions. Working closely with research and engineering colleagues, your primary focus will be on improving and developing new biometric technologies that are delivered on time and aligned with our strategic objectives. You will report directly to the Principal Research Scientist. Daon is a global leader in digital identity fraud prevention and protection against AI-generated synthetic identities. For over 25 years, we have partnered with governments and leading enterprises to deliver secure, seamless identity experiences across financial services, telecommunications, healthcare, travel, and critical infrastructure. Our TrustX platform enables organizations to orchestrate secure, scalable, cross-channel identity workflows — supporting identity verification, biometric authentication, and lifecycle management across complex environments. More than two billion identities worldwide have been safeguarded by Daon technology. Recognized as a leading provider by Gartner®, KuppingerCole, and Frost & Sullivan®, Daon is shaping the future of identity security. Daon has been providing fraud‑prevention solutions to organisations across six continents for over two decades. Come play a part in advancing the next generation of face liveness, matching, and anti‑fraud biometric technologies.

Requirements

Hands on experience in at least two of the following areas: Computer Vision & Deep Learning, Data & Experimental Methods, Image Recognition & Matching, Liveness & Anti-Spoofing.
A proven track record through project delivery, research contributions, or a minimum of two years of relevant employment experience.
Strong grounding in computer vision and machine learning principles
Proficiency with deep learning frameworks such as PyTorch or TensorFlow
Solid understanding of detection, recognition, and classical CV pipelines
Strong programming skills in Python and/or C++, including version control, testing, and debugging
Experience handling, preprocessing, and analysing large-scale datasets
Familiarity with synthetic data generation or weakly/lightly supervised learning approaches
Experience with authentication, identity matching, or metric learning
Knowledge of feature extraction, alignment, and embedding-based systems
Exposure to presentation attack detection, including replay, mask, or deepfake scenarios
Interest or experience in adversarial robustness and anti-spoofing research
Minimum English proficiency level of B2

Nice To Haves

Ability to review, interpret, and implement state-of-the-art research
Comfortable using AI tools to accelerate workflow and productivity
Awareness of privacy, ethics, and security considerations in biometrics
Strong written and verbal communication skills in English

Responsibilities

Developing machine learning algorithms for face authentication solutions
Researching, prototyping, and evaluating presentation attack detection and fraud prevention methods
Testing and configuring face algorithms to meet performance and accuracy standards
Extending and utilising existing biometric code libraries
Running rigorous experiments, interpreting findings, and translating outcomes into deployable models and policies
Helping to innovate and develop solutions to emerging face biometrics challenges
Applying and continuously growing your expertise in AI, machine learning, and computer vision