Staff Data Scientist (AI)

TL;DR

Staff Data Scientist (AI): Leading technical initiatives to transform high-scale telemetry into production-grade fraud and identity risk signals with an accent on adversarial modeling and complex data processing. Focus on defining rigorous evaluation methods, influencing telemetry collection, and mentoring data scientists to solve ambiguous, high-impact problems in the digital identity space.

Location: Must be based in the US (Hybrid: Miami, New York, San Francisco, Seattle, or Washington DC).

Compensation: $191,000 – $230,000 + equity + bonus.

Company

hirify.global is a leading provider of digital identity verification and fraud prevention solutions, utilizing AI and machine learning to power accurate identity trust decisions.

What you will do

• Lead high-impact machine learning and feature-development initiatives across device, network, and behavioral intelligence.
• Develop production risk signals that balance fraud detection, latency, explainability, and operational maintainability.
• Define evaluation methods including holdout design, leakage checks, and adversarial robustness monitoring.
• Translate complex fraud-risk questions into clear data science approaches and production-ready signal roadmaps.
• Mentor data scientists to improve problem framing, modeling judgment, and technical rigor.
• Influence data architecture, instrumentation, and product direction through technical leadership.

Requirements

• Master’s or Ph.D. in a quantitative field (Computer Science, ML, Statistics, etc.).
• 12+ years of experience in data science or applied machine learning.
• Significant experience building and deploying production ML models or risk signals.
• Strong background in fraud detection, trust and safety, or adversarial data domains.
• Expert-level SQL skills and proficiency in Python and distributed frameworks like Spark.
• Must be authorized to work in the US and able to work in a hybrid capacity at specified locations.

Nice to have

• Experience with device intelligence, behavioral biometrics, or graph-based risk signals.
• Familiarity with streaming or low-latency decisioning systems.
• Hands-on experience with ML frameworks such as XGBoost, TensorFlow, or PyTorch.
• Experience setting standards for model explainability and feature governance.

Culture & Benefits

• Total rewards package including base salary, equity, and annual bonus.
• Opportunity to solve complex, high-impact problems in the digital economy.
• Collaborative environment with a high bar for technical excellence and ownership.
• Commitment to diversity and equal opportunity employment.