Senior Fraud ML Engineer – Real‑Time Detection

Shoptalk; New York (NY); Hybrid; USD 159,000 - 230,000; Full time

Benefits offered by this job

Unlimited PTO

Employee stock options

Health plans with HSA

401k match

Parental leave

Home office stipend

Learning stipend

Well-being benefits

Hybrid work in NYC

Job summary

Alloy is seeking an experienced ML Researcher/Engineer to advance real-time fraud detection models and collaborate with customers to drive outcomes. You will design and evaluate ML systems, support end-to-end workflows, and ensure models stay accurate and compliant at scale.

You will work in a fast-paced, analytic environment with a strong emphasis on governance, documentation, and cross-team collaboration. Must be local to Greater NYC and willing to work hybrid onsite three days per week.

Qualifications

• 8+ years in Applied Fraud Research, Data Science, or ML in client-facing roles.
• Experience with imbalanced datasets and production-grade ML models (tree-based).
• Proficient in Python and SQL with data-scale thinking.
• Experience developing metrics and dashboards.
• Ability to communicate findings to technical and nontechnical audiences.
• Fast learner with analytical rigor and collaboration skills.
• Local to Greater New York City.

Responsibilities

• Design, train, and evaluate ML models for fraud detection.
• Create testing plans, metrics, and performance reports with actionable insights.
• Support production ML workflows: feature generation, training, monitoring.
• Document findings and share knowledge for continuous improvement.
• Maintain model documentation and governance alignment.
• Stay current with ML trends in fraud detection and risk management.

Skills

ML concepts

Python

SQL

Data wrangling

Metrics dashboards

Communicating findings

Analytical mindset

Education

Advanced degree preferred

Tools

Looker

Job description

Alloy is seeking an experienced ML Researcher/Engineer to advance real-time fraud detection models and collaborate with customers to drive outcomes. You will design and evaluate ML systems, support end-to-end workflows, and ensure models stay accurate and compliant at scale.

You will work in a fast-paced, analytic environment with a strong emphasis on governance, documentation, and cross-team collaboration. Must be local to Greater NYC and willing to work hybrid onsite three days per week.