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Nathan Redin is Head of Data at Neobrain, which he joined in 2020. He leads the team that collects, processes and structures the data powering Neobrain's platform, and contributes to product decisions and to the company's fundraising.

Specialized in natural language processing and deep learning, he develops and deploys machine learning models that analyze the job market, using language models (BERT), named-entity recognition and semantic embeddings (SentenceTransformers, spaCy), served through APIs. He built Neobrain's Data team, which brings together data scientists, data engineers, data analysts and a product owner.

Before Neobrain, he worked as a data scientist at Sia Partners (traffic modeling, computer vision), on credit default prediction in an R&D team at Neumann, as a market finance consultant at Accenture, and in trading and collateral management at HSBC.

A graduate of Télécom SudParis (Institut Polytechnique de Paris), where he earned an engineering degree in machine learning and applied statistics, and of Sciences Po (Master in Public Policy, specialization in digital, new technology and public policy), he combines technical depth with an understanding of the public policy issues raised by digital technology.

Find him on LinkedIn.

Artificial intelligence and data applied to HR:

Uses of generative AI and machine learning, natural language processing for skills analysis, People Analytics, HR data quality, and issues regarding ethics, bias, and compliance (GDPR, AI Act).

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