Data Scientist (Big Data R&D, Identity Graph & KYC)

Join Socure's Big Data R&D team as a Data Scientist, where you will develop graph-based algorithms and data pipelines on massive PII datasets, support modelers with high-quality features, and evaluate new data sources. You will work closely with senior data scientists and engineers, contributing to the design and implementation of machine learning, data mining, statistical, and graph-based algorithms. This is a fully remote position with comprehensive benefits, including health coverage, generous parental leave, and a self-education allowance.

• Contribuer à la conception et à la mise en œuvre d'algorithmes d'apprentissage automatique, d'exploration de données, statistiques et basés sur des graphes pour analyser de très grands ensembles de données.
• Analyser de grands ensembles de données pour aider à développer et à affiner les algorithmes de résolution d'entités et de correspondance d'identité qui alimentent les solutions KYC et de conformité de Socure.
• Construire et maintenir des composants de pipelines de traitement des données (ETL, génération de caractéristiques, normalisation) en utilisant des outils tels que Spark/PySpark et AWS.
• Hands‑on experience with Spark or PySpark and common ML libraries (e.g., scikit‑learn, XGBoost, TensorFlow/PyTorch a plus)
• Solid experience writing and optimizing SQL for large datasets; comfort working in data lake / warehouse environments
• Exposure to graph techniques or graph databases (Neo4j, AWS Neptune, GraphFrames) is a strong plus
• Bonus: experience with Elasticsearch or DynamoDB; workflow tools such as Airflow for automating data pipelines
• Familiarity with UNIX environments and the AWS ecosystem (e.g., EMR, S3); Databricks experience is a plus
• Proficiency in at least one general-purpose programming language used in data science (Python, or Scala)
• Ability to break down loosely defined problems, ask good clarifying questions, and iterate quickly with feedback
• Working knowledge of supervised/unsupervised ML and basic statistics (similarity measures, clustering, evaluation metrics)
• Master’s degree with 2+ years of experience, or Ph.D. with 1+ years of experience in a data science or analytics role, or equivalent practical experience