Data Scientist II (AI)

TL;DR

Data Scientist II (AI): Developing machine learning features, analytical methods, and production-oriented risk signals for identity verification and fraud prevention with an accent on high-cardinality telemetry and complex, noisy datasets. Focus on building scalable models, partnering with cross-functional teams to improve fraud detection, and ensuring system reliability in real-world production environments.

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

Salary: $140,000 – $170,000

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 for the digital economy.

What you will do

• Develop machine learning features, models, and analytical methods for device, network, and behavioral intelligence.
• Build features from large-scale, high-cardinality, and sparse telemetry data.
• Design and execute validation analyses, including drift assessment, leakage review, and customer impact analysis.
• Partner with engineering, product, and risk teams to implement features and support production rollouts.
• Contribute to model documentation, explainability materials, and production-readiness reviews.
• Support junior team members through code reviews and sharing modeling best practices.

Requirements

• Bachelor’s, Master’s, or Ph.D. in a quantitative field or equivalent experience.
• 5+ years of experience in data science, applied machine learning, or statistical modeling.
• Strong proficiency in Python and data science libraries (pandas, NumPy, scikit-learn, XGBoost, TensorFlow, PyTorch).
• Strong SQL skills and experience with large-scale, complex datasets.
• Experience with distributed data processing tools like Spark, PySpark, or Databricks.
• Ability to work independently on defined problem areas while collaborating with cross-functional stakeholders.

Nice to have

• Background in fraud detection, identity verification, trust and safety, or cybersecurity.
• Experience with device fingerprinting, behavioral biometrics, or network intelligence.
• Familiarity with production ML workflows, model monitoring, and real-time decisioning systems.
• Experience with graph features, embeddings, or representation learning.

Culture & Benefits

• Total rewards package includes base salary, equity, and annual bonus.
• Opportunity to work on high-impact, complex problems in the identity trust space.
• Collaborative environment working with senior data scientists and cross-functional partners.
• Focus on professional growth and developing technical judgment in production-grade AI systems.