Staff AI Scientist

Come join the Lending AI team at Intuit as a Staff AI Scientist. Lending AI builds the machine learning and AI systems behind Intuit's lending products - credit risk underwriting and decisioning, loan pricing and limit assignment, portfolio monitoring, and collections and loss forecasting. We use Intuit's proprietary small business and commercial financial data to underwrite customers no one else can see clearly, so that capital arrives in minutes instead of weeks.

Staff AI Scientists solve ambiguous problems and deliver end to end with a one-team mindset, spending 70% of their time on technical contributions. You will lead end-to-end aspects of complex lending applications or genuinely ambiguous problems - rearchitecting the underwriting decisioning stack, unifying credit signals across origination, or standing up cash flow underwriting for thin file small businesses. You will serve as a technical leader who influences product and technology decisions across multiple teams, including Credit Risk, Decisioning Engineering, and Servicing, and who keeps Intuit's lending AI differentiated.

Responsibilities

- Evaluate emerging research and introduce novel machine learning techniques to improve core lending metrics, such as net credit loss and loss forecasting accuracy.
- Lead the creation and governance of reusable credit data and feature assets, ensuring high data quality and compliance across teams.
- Design auditable and reproducible AI-first lending systems, including agentic flows for document intake, policy reasoning, and collections.
- Determine when to use LLM fine-tuning versus prompting based on decision quality, latency, cost, explainability, and risk management standards.
- Architect multi-stage agent pipelines and reusable science infrastructure to streamline experiment execution and results synthesis across teams.
- Solve complex research problems tailored to lending, such as learning from censored repayment outcomes and causal pricing optimization.
- Establish rigorous research standards, author papers on team innovations, and transfer research outputs into production underwriting and pricing systems.
- Orchestrate multi-team initiatives by managing dependencies across data, risk, and compliance, while steering technical plans through shifting market or regulatory conditions.
- Partner with Product, Credit Risk, Analytics, Legal, and Model Governance to ensure holistic AI integration across lending operations.
- Analyze customer journey data to identify unmet needs, such as expanding credit access for qualified thin-file small businesses.
- Define key success metrics and balance strategic trade-offs between approval rates, expected losses, unit economics, and overall portfolio health.
- Co-design end-to-end customer workflows with Product and Design, using experiment insights to shape the product roadmap.
- Mentor senior scientists, offer actionable technical feedback, and guide them in structuring work into reliable agent-executable components.
- Address foundational gaps in tech debt and tooling, build generalizable solutions, and lead hiring and mentoring plans to scale team impact.

Qualifications

- BS, MS, or PhD in Computer Science, Statistics, Mathematics, Economics, or a quantitative field (or equivalent experience).
- 8+ years of experience building, deploying, and leading cross-functional production ML systems.
- Proven track record of taking complex, high-stakes ML problems from concept to production with measurable business impact.
- Experience designing scalable data and feature platforms with versioning, quality contracts, lineage, and reproducibility.
- Strong communication skills to align cross-functional stakeholders (Product, Engineering, Risk) and communicate model designs to regulatory standards.
- Experience mentoring senior scientists and engineers.
- Good to have: Deep domain expertise in credit risk, underwriting policy, limit assignment, risk-based pricing, or loss forecasting.
- Good to have: Hands-on experience with LLMs and agentic systems, including orchestration, fine-tuning, RAG, and evaluation.

Intuit provides a competitive compensation package with a strong pay for performance rewards approach. This position may be eligible for a cash bonus, equity rewards and benefits, in accordance with our applicable plans and programs (see more about our compensation and benefits at Intuit®: Careers | Benefits ). Pay offered is based on factors such as job-related knowledge, skills, experience, and work location. To drive ongoing fair pay for employees, Intuit conducts regular comparisons across categories of ethnicity and gender.
The expected base pay range for this position is:
Mountain View $209,500 - $283,500