Workforce Risk Data Scientist (GenAI/NLP)

Socure; Seattle (WA); On-site; USD 140,000 - 170,000; Full time

Job summary

Socure’s RiskOS team is seeking a data scientist to own the end-to-end lifecycle for workforce risk use cases, focusing on Workforce Verification and fraud analytics. The role is based onsite in Seattle, WA, and requires collaboration across RiskOS, Workforce product teams, and engineering.

You will build ML models, rules, and GenAI components, work with large messy data, and contribute to productionizing models and evaluation frameworks.

Qualifications

• 4+ years of hands-on data science, ML, or analytics work, in fraud/risk or workforce analytics preferred.
• Proficiency with Python and SQL; experience with ML libraries and pipelines.
• Experience owning end-to-end analytics projects from framing to deployment.
• Exposure to NLP and unstructured text analytics in real products.
• Hands-on experience with Generative AI, LLM APIs, RAG, or evaluation of AI outputs.

Responsibilities

• Own the full data science lifecycle for Workforce Verification use cases within RiskOS.
• Explore workforce-related data sources (applications, resumes, device telemetry, background checks).
• Design, implement, and iterate on rules and heuristics in RiskOS workflows.
• Develop and evaluate ML models for workforce risk and identity assessment.
• Collaborate on GenAI features like the Resume Verification Agent; define inputs/outputs and evaluation frameworks.
• Work with engineering to productionize models, rulesets, and GenAI components.
• Translate model performance into customer-facing narratives with stakeholders.
• Incorporate feedback and experimentation to improve logic and models.
• Document assumptions and decisions; communicate risks and opportunities.

Skills

Python

SQL

pandas

scikit-learn

XGBoost

PySpark

NLP

Generative AI

LLM APIs

data engineering

Education

Bachelor's or Master's in a quantitative field

Tools

Airflow

Spark

ETL

JSON

Job description

Socure’s RiskOS team is seeking a data scientist to own the end-to-end lifecycle for workforce risk use cases, focusing on Workforce Verification and fraud analytics. The role is based onsite in Seattle, WA, and requires collaboration across RiskOS, Workforce product teams, and engineering.

You will build ML models, rules, and GenAI components, work with large messy data, and contribute to productionizing models and evaluation frameworks.