# Data Scientist ll - RiskOS at Socure

- Company: Socure
- What the company does: Socure is the leading AI-powered identity verification platform trusted by 3,000+ customers to verify consumers, businesses, & employees with confidence. Backed by Accel.
- Company website: https://www.socure.com/
- Type: Startups
- Level: Mid level
- Location: Hub - Miami
- Work setup: Remote
- Pay: $140K to $170K base salary per year (USD)
- Posted: 2026-09-17
- Apply by: 2026-11-01
- Apply: https://jobs.ashbyhq.com/socure/5337e747-bc84-4c2d-8f5e-042cf64bc80e
- Page: https://www.1752.vc/careers/jobs/socure-data-scientist-ll-riskos/

## About the role

Socure is the leading provider of digital identity verification and fraud prevention solutions, leveraging AI and machine learning to power the most accurate decisions. Our mission is to eliminate identity fraud and ensure online trust across industries. RiskOS is Socure’s AI-powered orchestration and decisioning platform, providing a centralized control plane for identity, fraud, and risk workflows across the customer lifecycle.

## What they're looking for

- Bachelor’s or Master’s degree in Computer Science, Statistics, Mathematics, Engineering, or a related quantitative field, or equivalent practical experience
- 3–6 years of hands-on experience in data science, machine learning, or applied analytics, with meaningful work on fraud, risk, trust & safety, or workforce/hiring analytics preferred
- Experience owning end-to-end analytics and/or model development projects: problem framing, data wrangling, feature engineering, model training, evaluation, and deployment support
- Strong proficiency in Python and SQL, including experience with common data science and ML libraries (e.g., pandas, scikit-learn, XGBoost, PySpark, or similar)
- Comfort working with large, messy, and heterogeneous datasets (JSON workflows, logs, event streams, third-party enrichments) and building reusable abstractions or utilities to make them usable for yourself and others
- Exposure to Natural Language Processing and/or unstructured text analytics—such as resume or document parsing, entity extraction, similarity search, or basic embedding-based methods—ideally applied in real-world products

Tags: AI and Data