Senior AI Scientist (Fintech)

TL;DR

Senior AI Scientist (Fintech): Developing cutting-edge credit risk AI/ML models for new lending products with an accent on hands-on ownership of the model lifecycle and driving the data strategy across all involved teams. Focus on designing, building, deploying, evaluating, and monitoring machine learning models to predict credit risk for various short-term lending products.

Location: Oakland, Charlotte, Culver City, San Diego, London, Bangalore, and New York City

Salary: $173,500.00 - 234,500.00

Company

hirify.global is a mission-driven company, focused on championing financial progress for its more than 140 million members globally.

What you will do

• Design, build, deploy, evaluate, and monitor machine learning models to predict credit risk for various short-term lending products.
• Collaborate with credit policy, product, and fraud risk teams to ensure models align with business goals and product offering to drive actionable lending decisions.
• Build efficient and reusable data pipelines for feature generation, model development, scoring, and reporting using Python, SQL, and both commercially available and proprietary Machine Learning and AI infrastructures.
• Contribute to the evolution of our data and machine learning infrastructure within the Intuit ecosystem to improve the efficiency and effectiveness of AI science solutions.

Requirements

• Advanced Degree (Ph.D. / MS) in Computer Science, Data Science, AI, Mathematics, Statistics, Physics, or a related quantitative discipline.
• 6+ years of work experience in AI Science / Machine Learning and related areas.
• Authoritative knowledge of Python and SQL.
• Relevant work experience in fintech credit risk, with a deep understanding of payment systems, money movement products, banking, and lending.
• Experience leveraging credit bureau, tax, and cash flow data in credit risk model development.
• Deep understanding of credit risk modeling concepts, including PD calibration, reject inference, adverse action logic, and risk segmentation.

Nice to have

• Proficiency in deep learning ML frameworks such as TensorFlow, PyTorch, etc.
• Work experience with public cloud platforms (especially GCP or AWS) and workflow orchestration tools like Apache Airflow.
• Strong background in MLOps infrastructure and tooling, particularly Vertex AI or AWS SageMaker, including pipelines, automated retraining, monitoring, and version control.

Culture & Benefits

• Experience professional growth and encourage growth throughout the team
• Work cross-functionally to ensure the efficient and effective use of data science in ways that make an immediate, substantial, and sustainable impact.
• Generous benefits and perks with a single eye to nourishing an inclusive environment that recognizes the contributions of all and fosters diversity by supporting our internal Employee Resource Groups.