Senior AI Scientist
Intuit
Senior AI Scientist
Intuit
Tax, accounting, and personal-finance software
Intuit is the global financial technology platform that powers prosperity for the people and communities we serve. With tens of millions of customers worldwide using products such as TurboTax, Credit Karma, QuickBooks, and Mailchimp, we believe that everyone should have the opportunity to prosper. We never stop working to find new, innovative ways to make that possible.
Intuit's Business Intelligence (BI) team builds the reporting and analytics experiences that millions of QuickBooks customers and accountants rely on every day, including Modern Reports, Management Reports, KPI Scorecards, Dashboards, and FP&A (Cash Flow, Budgets, Forecasting). The team is in the middle of extending these experiences with AI: conversational reporting through Omni, self-serve report building, and agentic development practices that let us build faster on a codebase spanning years of financial logic. We sit on one of Intuit's largest proprietary datasets, tens of billions of transaction rows across millions of small businesses, and we are scaling our platform (built on StarRocks) to support multi-entity, multi-currency customers at a new order of magnitude.
As a Senior AI Scientist on BI, you will own AI/ML solutions end to end, from data curation through evaluation to production, applied directly to BI's reporting and financial-analysis surfaces. You will work closely with BI's product, design, and engineering teams to bring machine learning and LLM-based approaches to problems like generating financial narratives, surfacing benchmarking insights on KPI Scorecards, and improving forecasting for Cash Flow and Budgets.
Responsibilities
Own delivery of end-to-end AI/ML solutions for BI surfaces, spanning modeling, evaluation, and production integration.
Select appropriate algorithms and approaches for financial and reporting problems, explain trade-offs, and identify common failure modes such as hallucination, bias, and drift.
Curate task-specific datasets from Intuit's proprietary financial data, with data governance and privacy built in, and build evaluation benchmarks specific to BI use cases, such as the accuracy of generated financial commentary or KPI explanations.
Design AI-native features that balance latency, cost, and quality, including features embedded in agentic pipelines such as Omni conversational BI, and design evaluation approaches for non-deterministic agentic flows.
Track emerging research and apply novel ML methods, including causal inference, time-series forecasting, and NLP/LLMs, to BI problems such as anomaly detection in financial statements and multi-entity consolidation insights.
Use AI agents as part of your own science workflow, including experiment orchestration, hyperparameter search, and simulation-based validation, and help set standards for which BI science tasks should be agent-driven.
Partner with BI product, design, and engineering to shape what's worth building, grounded in usage and feedback signals from reporting surfaces.
Apply responsible AI practices given that BI surfaces present financial figures directly to accountants and business owners, and mentor others on the same.
Qualifications
MS or PhD in Computer Science, Statistics, Applied Mathematics, Operations Research, or a related field, or equivalent practical experience.
4+ years of applied ML or data science experience, ideally including work with financial, accounting, or structured tabular and time-series data.
Hands-on experience with LLMs and agentic AI systems, including prompting, fine-tuning, and evaluation of agent pipelines, alongside classical ML methods such as supervised and unsupervised learning, time-series forecasting, and anomaly detection.
Proficient in Python and SQL, comfortable in a Linux environment, and experienced with large-scale distributed data systems such as Spark or Hive; familiarity with OLAP engines such as StarRocks is a plus.
Experience building end-to-end, reusable ML pipelines, from data acquisition and ETL through model deployment and monitoring.
Strong written and verbal communication skills, with the ability to explain technical and financial concepts to both technical and non-technical audiences.
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.
Own delivery of end-to-end AI/ML solutions for BI surfaces, spanning modeling, evaluation, and production integration.
Select appropriate algorithms and approaches for financial and reporting problems, explain trade-offs, and identify common failure modes such as hallucination, bias, and drift.
Curate task-specific datasets from Intuit's proprietary financial data, with data governance and privacy built in, and build evaluation benchmarks specific to BI use cases, such as the accuracy of generated financial commentary or KPI explanations.
Design AI-native features that balance latency, cost, and quality, including features embedded in agentic pipelines such as Omni conversational BI, and design evaluation approaches for non-deterministic agentic flows.
Track emerging research and apply novel ML methods, including causal inference, time-series forecasting, and NLP/LLMs, to BI problems such as anomaly detection in financial statements and multi-entity consolidation insights.
Use AI agents as part of your own science workflow, including experiment orchestration, hyperparameter search, and simulation-based validation, and help set standards for which BI science tasks should be agent-driven.
Partner with BI product, design, and engineering to shape what's worth building, grounded in usage and feedback signals from reporting surfaces.
Apply responsible AI practices given that BI surfaces present financial figures directly to accountants and business owners, and mentor others on the same.
Qualifications
MS or PhD in Computer Science, Statistics, Applied Mathematics, Operations Research, or a related field, or equivalent practical experience.
4+ years of applied ML or data science experience, ideally including work with financial, accounting, or structured tabular and time-series data.
Hands-on experience with LLMs and agentic AI systems, including prompting, fine-tuning, and evaluation of agent pipelines, alongside classical ML methods such as supervised and unsupervised learning, time-series forecasting, and anomaly detection.
Proficient in Python and SQL, comfortable in a Linux environment, and experienced with large-scale distributed data systems such as Spark or Hive; familiarity with OLAP engines such as StarRocks is a plus.
Experience building end-to-end, reusable ML pipelines, from data acquisition and ETL through model deployment and monitoring.
Strong written and verbal communication skills, with the ability to explain technical and financial concepts to both technical and non-technical audiences.
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.
Intuit provides financial technology tools for consumers and small businesses. Its main products are TurboTax for tax preparation, QuickBooks for accounting, and Mint for personal finance management. These tools typically operate on a subscription basis or behind transaction fees, with features that help users file taxes, track income and expenses, and manage budget and goals. The software ecosystem is designed to connect tax, accounting, and personal finance in one place, improving workflows for individuals, freelancers, and small business owners. Security is a priority, with measures like multi-factor authentication and anti-fraud protections to protect user data. Intuit’s goal is to help people achieve financial well-being by educating users and delivering easy-to-use, reliable financial software across different needs and customer segments.
Explore more opportunities at Intuit