Data Scientist II - Global Watchlist
Role details
Job location
Tech stack
Job description
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., * 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.
Requirements
Do you have experience in Statistical significance testing?, Do you have a Master's degree?, * 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., * 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.