Data Scientist II – Global Watchlist
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Job Description
Data Scientist II at Socure bridging Watchlist R&D and Customer Applications teams. Accelerating model deployment through automated frameworks and monitoring systems for identity verification.
Responsibilities:
- 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 and POC findings 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:
- 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.
- Strong programming skills in Python and SQL, with hands-on experience in Spark and Databricks.
- Experience with Airflow for orchestration and a working knowledge of Infrastructure as Code (e.g., Terraform) and AWS environments.
- Solid grasp of descriptive statistics, hypothesis testing, and model evaluation metrics (Precision, Recall, F-beta, ROC-AUC).
- Practical experience in data curation, labeling strategies, and building automated data-quality validation checks.
- Excellent ability to communicate complex technical findings to both R&D peers and non-technical stakeholders.
- 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 is preferred.
- Background in AML (Anti-Money Laundering), Sanctions Screening, or Identity Fraud prevention is preferred.
- Prior experience in a "Customer Data Science" or "Solutions DS" role where you built tools for internal or external stakeholders is preferred.
Benefits:
- Offers Equity
- Offers Bonus
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