Senior Credit Risk AI Scientist (Fintech)

TL;DR

Senior Credit Risk AI Scientist (Fintech): Designing, building, and maintaining machine learning models to predict and prevent fraud and financial risk in consumer money products with an accent on owning the full model lifecycle and program-level outcomes. Focus on applying innovative machine learning and statistical approaches to dynamic, real-world fraud challenges and contributing to scalable ML and data infrastructure.

Location: Mountain View, California; New York, New York

Salary: $172,000–$232,500 (New York)

Company

hirify.global is a global financial technology platform powering prosperity for approximately 100 million customers worldwide with products like TurboTax, Credit Karma, QuickBooks, and Mailchimp.

What you will do

• Design, build, evaluate, monitor, and maintain machine learning models for fraud and financial risk prediction in consumer money products.
• Collaborate with cross-functional teams (product, policy, engineering, partners) to understand business problems and design ML solutions.
• Lead fraud/financial risk modeling for evolving consumer money products, owning the full model lifecycle and program-level outcomes.
• Contribute to the technical strategy and decisioning roadmap for risk across multiple product lines.
• Contribute to the development of scalable ML and data infrastructure.
• Research and apply innovative machine learning and statistical approaches for dynamic fraud challenges.

Requirements

• Advanced Degree (MS or higher) in Computer Science, Data Science, AI, Mathematics, Statistics, Physics, or a related quantitative discipline.
• 3+ years of experience in Data Science / Machine Learning and related areas.
• Deep understanding of various machine learning techniques (deep learning, tree-based models, reinforcement learning, clustering, time series, causal analysis, NLP).
• Proficiency in deep learning ML frameworks (TensorFlow, PyTorch).
• Expertise in designing and building efficient and reusable data pipelines and frameworks for ML models.
• Authoritative knowledge of Python and SQL.
• Strong business problem-solving, communication, and collaboration skills.

Nice to have

• Relevant work experience in money fraud/credit risk, with deep understanding of money movement products, banking, finance, credit bureau, and fraud detection data.
• Experience in graph modeling, experimentation design, public cloud platforms (AWS or GCP), Apache Airflow, Vertex AI, unsupervised ML, anomaly detection, Scala.
• Experience in MLOps infrastructure and tooling.

Culture & Benefits

• Competitive compensation package with a strong pay-for-performance rewards approach.
• Eligible for cash bonus, equity rewards, and benefits.
• Regular pay comparisons across categories of ethnicity and gender to ensure fair pay.