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.