Senior Staff AI Scientist

Intuit; Anchorage (AK); On-site; USD 226,000 - 306,000; Full time

Job summary

Intuit is seeking a Senior Staff AI Scientist to advance probabilistic forecasting for cash flow and financial forecasting across QuickBooks Fintech. You will own models from concept to production, collaborating with data teams and product partners to define metrics and drive business impact.

The role emphasizes leadership, hands-on modeling, and building scalable AI systems with a focus on performance, latency, and calibration of forecasts.

Qualifications

• 8+ years in applied ML/AI delivering scalable AI systems.
• Hands-on with time-series forecasting and probabilistic methods.
• Experience leading a tech scrum team and shipping production models.

Responsibilities

• Design, train, and deploy large-scale forecasting models end-to-end.
• Lead AI science efforts and evangelize across the org.
• Collaborate with product, eng, and design to define success criteria.
• Mentor scientists, ensure high-quality code and costs discipline.

Skills

Time-series modeling

Probabilistic forecasting

Transformer architectures

Production ML systems

Leadership

Distributed training

Data mining / NLP

Model evaluation & calibration

Education

PhD/MS in Statistics, CS, OR

Tools

PyTorch

TensorFlow

Spark / SQL

Job description

We're scaling the AI science behind QuickBooks' financial intelligence platform, and we're looking for a Senior Staff AI Scientist to build the probabilistic forecasting models that power cash flow prediction and financial forecasting for millions of small businesses.

Being part of QuickBooks Fintech means you'll sit at the center of decisions that directly shape small business financial health. You'll work closely with data pipeline and infrastructure teams to take models from concept to trained, calibrated, production-ready systems.

Responsibilities

• Design, implement, and train large-scale forecasting models end-to-end in code.

• Practices leadership and communication skills to influence teams and to evangelize AI science across the organization

• Collaborates with stakeholders to define success criteria and align model metrics with business goals. Works side-by-side with product managers, software engineers, and designers in designing experiments and minimum viable products

• Leads technical work of a scrum team: initiating and designing model solutions, driving end-to-end architecture designs of the team’s work, and holding the team accountable for high quality code, git, design, costs and implementation standards

• Performs hands-on data analysis and modeling with large data sets, including discovering data sources, getting data access, cleaning up data, and making them “model-ready”. You need to be willing and able to do your own ETL and design/build featurization.

• Applies data mining, NLP, and machine learning (such as supervised/unsupervised, Causal-ML, Online Learning, Bayesian Learning, Reinforcement Learning, or Deep Learning) to real-world problems and datasets

• Mentor other scientists and engineers, contributing to a high-performance, inclusive AI science community that promotes innovation and craft excellence.

• Communicate AI tradeoffs and strategy clearly to technical and non-technical leaders. Influence roadmaps with data, insights, and a deep understanding of customer needs.

Qualifications

• 8+ years of experience in applied ML/AI, with a strong track record of delivering scalable, production-grade AI systems.

• BS, MS or PhD in Statistics, Mathematics, Computer Science, Economics, Operations Research, or equivalent

• Deep hands-on experience building and training time-series or sequence models for multi-horizon probabilistic forecasting (e.g., transformer-based forecasters such as TFT, DeepAR, or N-BEATS/N-HiTS, or comparable architectures).

• Strong applied grounding in probabilistic forecasting: quantile or distributional loss functions, calibration evaluation, and multi-task objectives across several targets.

• Experience building large-scale learned representations (e.g., entity embeddings at millions-of-entities scale), including cold-start strategies.

• Strong fundamentals in a modern deep learning framework, with experience building production training and inference pipelines.

• Experience optimizing models for production latency and throughput constraints, from real-time inference to large-batch scoring.

• Excellent communication skills and the ability to work effectively with both technical and non-technical partners, including risk and compliance stakeholders.

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 $226,000 - $306,000