Senior Data Scientist (Machine Learning)

TL;DR

Senior Data Scientist (Machine Learning): Building and improving production machine learning systems for document verification, fraud detection, biometric verification, and product analytics with an accent on computer vision, model evaluation, and scalable ML tooling. Focus on designing experiments, monitoring model health, analyzing attack vectors, and translating data insights into product and fraud-prevention decisions.

Location: Hybrid in San Francisco, Miami, New York, or Seattle, United States

Salary: $191,000–$230,000 base salary annually, plus equity, benefits, and an annual bonus or commission plan.

Company

hirify.global builds identity trust infrastructure for the digital economy, verifying identities and preventing fraud for businesses, governments, and consumers.

What you will do

• Design, develop, and improve production ML models for document verification, fraud detection, image quality assessment, and biometric verification.
• Research new features, modeling approaches, and fraud detection techniques to improve production performance.
• Partner with Engineering to deploy, monitor, and continuously improve models.
• Evaluate models using offline and production datasets, measuring precision, recall, FAR/FRR, and business impact.
• Analyze product performance, fraud trends, customer behavior, and emerging attack vectors.
• Build dashboards, KPIs, automation, labeling workflows, and self-service experimentation tools.

Requirements

• MS, PhD, or equivalent experience in Computer Science, Statistics, Data Science, or a related field.
• 5+ years of experience in machine learning, data science, fraud analytics, or product analytics.
• Strong experience developing and evaluating production ML models.
• Expert Python and SQL skills.
• Experience with Databricks, Spark, AWS SageMaker, or similar platforms.
• Strong knowledge of experimentation, statistical analysis, ML evaluation, computer vision, deep learning, or transformer-based models.

Culture & Benefits

• Work on identity verification and fraud prevention products with broad customer and societal impact.
• Collaborate across Product, Engineering, Fraud Operations, Data Science, and Solutions Engineering.
• Compensation includes base salary, equity, benefits, and an annual bonus or commission plan.
• Inclusive equal opportunity workplace with accommodations available throughout the hiring process.