Senior AI Scientist (Fintech)

TL;DR

Senior AI Scientist (Fintech): Leading the evolution of financial recommendation engines, understanding, predicting, and acting on member intent. Focus on building a holistic map of the member’s financial journey, ensuring perfectly timed and deeply personalized recommendations.

Location: Oakland, California

Salary: $180,000 - 243,500

Company

hirify.global is the global financial technology platform that powers prosperity for the people and communities we serve.

What you will do

• Lead the development of large-scale models that predict member needs across multiple financial verticals.
• Build recommendation logic that balances immediate revenue with long-term member trust and lifetime value.
• Collaborate with partner teams to define metrics that quantify various aspects of the business.
• Represent Data Science in cross-functional meetings and reviews, translating technical subject matter to business partners.

Requirements

• MS in Computer Science, Mathematics, Statistics, Physics, or a related quantitative discipline.
• 5+ years of experience building and deploying machine learning models in a production environment (ideally in consumer tech, fintech, or e-commerce).
• Expert proficiency in Python and SQL, with deep experience in modern ML/DL frameworks.
• Experience with ranking, retrieval, and multi-stage recommendation architectures.
• Proven ability to explain complex AI concepts to non-technical stakeholders and link model performance to business outcomes.

Culture & Benefits

• Solve challenges ranging from Deep Learning and Reinforcement Learning to recommendation and GenAI for Personal Finance Products.
• Be part of a highly impactful team working on large-scale projects that directly impact the business and members.
• Value scientists who act like owners—identifying problems, proposing solutions, and seeing them through to production.
• Gain experience with driving monetization, member engagement, and longer-term member value through AI.
• Work on large-scale AI systems with applications across machine learning and generative AI, AI infrastructure, data foundation, and self-serve analytics through DS methods.
• Balance fast-paced environments at a large-scale company.