Data Scientist II - Global Watchlist

WHY SOCURE? Socure is building the identity trust infrastructure for the digital economy — verifying 100% of good identities in real time and stopping fraud before it starts. The mission is big, the problems are complex, and the impact is felt by businesses, governments, and millions of people every day. We hire people who want that level of responsibility. People who move fast, think critically, act like owners, and care deeply about solving customer problems with precision. If you want predictability or narrow scope, this won’t be your place. If you want to help build the future of identity with a team that holds a high bar for itself — keep reading. ABOUT THE ROLE As a Data Scientist II at Socure, you will occupy a high-impact, "bridge" role between our core Watchlist R&D and the Data Science Customer Applications (DSCA) teams. Your mission is to accelerate the transition from model development to real-world deployment by building the automated analysis frameworks and monitoring systems that drive customer success. You won’t just build models; you will create the technical connective tissue—including high-performance pipelines and custom dashboards—that allows Socure to onboard clients faster, resolve complex issues effectively, and continuously improve our models through a closed-loop feedback system. WHAT YOU'LL DO - Develop Analysis Frameworks: Design and maintain scalable frameworks that allow the DSCA team to perform fast, effective client resolutions during POCs, onboarding, and for existing production customers. - Bridge R&D and Operations: Act as the primary technical liaison between Watchlist DS and DSCA, translating complex model behaviors into actionable insights for customer-facing teams. - Build Monitoring & Alerting Systems: Create and manage mission-critical dashboards and real-time alert systems to monitor model performance, identify drift, and surface false positives/negatives at a sub-segment level. - Drive Closed-Loop Model Improvement: Systematically monitor customer production data to integrate real-world feedback back into the core model development cycle. - Enhance In-House Pipelines: Build and optimize end-to-end data pipelines (using Spark and Airflow) that support custom reporting and automated performance tracking for Watchlist POCs. - Collaborate Cross-Functionally: Work closely with Product, Engineering, and Compliance to translate customer needs and regulatory requirements into measurable machine-learning objectives. WHAT YOU BRING - Education: Bachelor’s degree in a quantitative field (Computer Science, Statistics, Mathematics, or similar) with 3–5 years of experience —or— a Master’s/Ph.D. with 1–3 years of experience. - Technical Proficiency: Strong programming skills in Python and SQL, with hands-on experience in Spark and Databricks. - Pipeline & Infrastructure: Experience with Airflow for orchestration and a working knowledge of Infrastructure as Code (e.g., Terraform) and AWS environments. - Analytical Rigor: Solid grasp of descriptive statistics, hypothesis testing, and model evaluation metrics (Precision, Recall, F-beta, ROC-AUC). - ML & Data Engineering: Practical experience in data curation, labeling strategies, and building automated data-quality validation checks. - Communication & Impact: Excellent ability to communicate complex technical findings to both R&D peers and non-technical stakeholders. - Passion for the Domain: A strong interest in NLP, LLMs, and staying ahead of the curve in compliance and regulatory technology. PREFERRED QUALIFICATIONS - Experience with Elasticsearch and real-time data indexing. - Background in AML (Anti-Money Laundering), Sanctions Screening, or Identity Fraud prevention. - Prior experience in a "Customer Data Science" or "Solutions DS" role where you built tools for internal or external stakeholders. Please note that sponsorship is not available at this time. Socure is an equal opportunity employer that values diversity in all its forms within our co