Data Scientist (Workforce Verification, RiskOS)

Location: Hybrid; hubs in Miami, New York, San Francisco, and Seattle

Base salary: $140,000–$170,000 annually, plus equity and an annual bonus or commission plan.

Company

hirify.global builds AI-powered digital identity verification and fraud prevention solutions, including the RiskOS orchestration and decisioning platform.

What you will do

• Own the end-to-end data science lifecycle for Workforce Verification use cases, from exploration and hypothesis generation through deployment and monitoring.
• Analyze applications, resumes, device and behavioral telemetry, background checks, and ATS/HRIS data to identify workforce identity fraud.
• Design rules, conditions, heuristics, and machine learning models for applicant fraud risk, identity relationships, and anomalous hiring flows.
• Develop and evaluate GenAI features such as resume verification and explanation agents, including datasets and quantitative and qualitative evaluation frameworks.
• Partner with engineering to productionize models, rulesets, and GenAI components, including interfaces, testing, monitoring, alerting, and feedback loops.
• Translate model performance and customer feedback into improved workflows, test harnesses, and customer-facing explanations.

Requirements

• 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; fraud, risk, trust and safety, or workforce analytics experience is preferred.
• Strong Python and SQL skills with experience using data science and machine learning libraries such as pandas, scikit-learn, XGBoost, or PySpark.
• Experience with data wrangling, feature engineering, model training, evaluation, deployment support, and large heterogeneous datasets.
• Experience or exposure to NLP, unstructured text analytics, Generative AI, or LLM-based products, including prompt design, commercial LLM APIs, RAG, or output evaluation.
• Ability to contribute to data engineering and production-oriented work, communicate complex analyses clearly, and collaborate with product, engineering, GTM, and customers.

Nice to have

• Experience with workforce, HR tech, ATS/HRIS data, or hiring funnel analytics.
• Experience with identity verification, device intelligence, or orchestration and rules engines.
• Familiarity with GenAI evaluation and monitoring, offline benchmarks, human-in-the-loop review, and hallucination or safety checks.

Culture & Benefits

• Work in a fast-paced environment with broad ownership and increasing scope.
• Collaborate closely with senior data scientists, product, engineering, Workforce GTM, and solution consulting.
• Compensation includes equity, benefits, and an annual bonus or commission plan.
• Support is available for accommodations during the application and hiring process.