Senior Data Scientist (International eKYC, Identity Graph)

About the role

Join Socure, a leading provider of digital identity verification solutions. As a Senior Data Scientist, you will drive the development of global identity verification solutions, focusing on international eKYC. You will design and deploy machine learning and graph-based systems tailored to diverse international markets and regulations. You will collaborate with cross-functional teams to launch and scale eKYC solutions across multiple countries and regions. Key missions: Conception et déploiement de systèmes d'apprentissage automatique et basés sur des graphes adaptés à divers marchés internationaux.. Responsabilité pour des initiatives complexes et transversales, telles que l'évolution du graphe d'identité international et le rapprochement probabiliste.. Partenariat étroit avec les équipes Produit, Ingénierie, Conformité et GTM pour lancer et développer des solutions eKYC. Profile: - 6+ years of hands-on applied ML / data science experience (4+ with Ph.D.), including owning production models and pipelines in high‑stakes domains (fraud, risk, identity, payments, credit, or similar) - Significant prior work on international or multi‑region products is strongly preferred (e.g., cross‑country KYC, credit risk, payments, or compliance systems) - Master’s or Ph.D. in Computer Science, Data Science, Machine Learning, Statistics, Mathematics, or a related field, or equivalent practical experience - Feature engineering for noisy/heterogeneous identity data - Proven expertise with graph technologies (e.g., Neo4j, AWS Neptune, GraphFrames, DGL, PyTorch Geometric) and graph algorithms (entity resolution, link prediction, community detection, label propagation) at scale - Expert‑level proficiency in Python and SQL, with extensive experience in distributed data processing (Spark/PySpark, Databricks or similar) on very large datasets - Robust evaluation under label sparsity and feedback delays - Deep experience designing, training, and deploying models for classification, ranking, anomaly detection, and/or graph learning, including: - Calibration and thresholding tailored to regional risk and regulatory constraints