Data Scientist II: Workforce Verification in RiskOS

Socure; Miami (FL); On-site; USD 140,000 - 170,000; Full time

Job summary

Socure is the leading provider of digital identity verification and fraud prevention solutions. We are seeking a Data Scientist for Workforce Verification on the RiskOS team to own end‑to‑end data science work, from data exploration to productionized models handling resumes, applications, and device signals.

You will collaborate with product and engineering on GenAI‑powered components, evaluation frameworks, and productionization, while analyzing rich, unstructured data to uncover fraud patterns

Qualifications

• 3–6 years of hands‑on data science, ML, or analytics experience, with fraud/risk exposure preferred.
• Experience owning end‑to‑end analytics and model development projects.
• Strong Python and SQL skills; familiar with ML libraries.

Responsibilities

• Own the full data science lifecycle for Workforce Verification in RiskOS—from exploration to deployment and monitoring.
• Analyze workforce data sources to identify patterns of fraud such as fake resumes and identity rental.
• Design and iteratively improve rules, heuristics, and ML models for workforce risk.
• Collaborate on GenAI features like Resume Verification Agent and explanation agents.
• Work with engineering to productionize models and monitor performance.

Skills

Python

SQL

NLP

Generative AI

Data analysis

Machine learning

ETL

PySpark

Pandas

scikit-learn

XGBoost

Education

Bachelor’s or Master’s degree in Computer Science/Statistics/Mathematics/Engineering

Tools

Pandas

scikit-learn

XGBoost

PySpark

Job description

Socure is the leading provider of digital identity verification and fraud prevention solutions. We are seeking a Data Scientist for Workforce Verification on the RiskOS team to own end‑to‑end data science work, from data exploration to productionized models handling resumes, applications, and device signals.

You will collaborate with product and engineering on GenAI‑powered components, evaluation frameworks, and productionization, while analyzing rich, unstructured data to uncover fraud patterns