On the AI/ML data science team at Intuit, you'll lead technical work and influence cross-functional teams by defining success criteria with stakeholders, designing end-to-end model solutions and architectures, and ensuring high-quality code, design, cost, and implementation standards. You will work closely with product managers, engineers, and designers to build experiments and MVPs, perform hands-on data analysis and modeling—including sourcing, cleaning, and preparing large datasets—and apply advanced ML techniques such as NLP, causal inference, online and Bayesian learning, reinforcement learning, and deep learning to real-world problems. You’ll also run A/B tests, communicate results and integration plans with partners, and proactively research and evangelize new ML technologies and academic/industry developments to solve Intuit customer problems.
Commitments
You need to be willing and able to own your ETL pipelines and independently design and build feature engineering workflows.
Responsibilities
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.
Runs A/B tests to draw conclusions on the impact of your team’s work and communicates results to peers and leaders
Communicates with partners to ensure successful delivery and integration of DS solutions.
Proactively researches, explores, and enables new ML technologies.
Keeps up with the new developments in academia and industry and considers possible extensions to solve Intuit customer problems.
Commitments
You need to be willing and able to do your own ETL and design/build featurization.
Not Met Priorities
What still needs stronger evidence
Requirements
You need to be willing and able to do your own ETL and design/build featurization.
6+ years of industry experience with AI science
4+ years of hands-on expertise in ML paradigms such as Causal-ML, supervised/unsupervised, Online, Bayesian, Reinforcement or Deep Learning.
Proficient in multiple optimization paradigms such as combinatorial optimization, gradient methods, or Bayesian optimization.
Proficient in NLP techniques, Explainable AI, and ML frameworks.
Expertise in modern advanced analytical tools and programming languages such as Python, Scala, Java and/or R.
Efficient in SQL, Hive, SparkSQL, etc.
Comfortable working in a Linux environment
Experience with building end-to-end reusable pipelines from data acquisition to model output delivery
Quick learner, adaptable, with the ability to work independently in a fast-paced environment
Strong oral and written communication skills.
Ability to conduct meetings and make professional presentations, and to explain complex concepts and technical material to non-technical users
Preferred Skills
Efficient in SQL, Hive, SparkSQL, etc.
Education
(Not required)
– BS, MS or PhD in Statistics, Mathematics, Computer Science, Economics, Operations Research, or equivalent
Overview Intuit is looking for innovative and hands-on Senior Staff AI Scientist to join the Intuit AI team. Come join our collaborative and creative group of AI scientists and machine learning engineers and build models that directly affect hundreds of thousands of our customers. In this role you will be building and deploying machine learning models using both analytical algorithms and deep learning approaches. Responsibilities
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. Runs A/B tests to draw conclusions on the impact of your team’s work and communicates results to peers and leaders Communicates with partners to ensure successful delivery and integration of DS solutions. Proactively researches, explores, and enables new ML technologies. Keeps up with the new developments in academia and industry and considers possible extensions to solve Intuit customer problems. Qualifications
6+ years of industry experience with AI science BS, MS or PhD in Statistics, Mathematics, Computer Science, Economics, Operations Research, or equivalent 4+ years of hands-on expertise in ML paradigms such as Causal-ML, supervised/unsupervised, Online, Bayesian, Reinforcement or Deep Learning. Proficient in multiple optimization paradigms such as combinatorial optimization, gradient methods, or Bayesian optimization. Proficient in NLP techniques, Explainable AI, and ML frameworks. Expertise in modern advanced analytical tools and programming languages such as Python, Scala, Java and/or R. Efficient in SQL, Hive, SparkSQL, etc. Comfortable working in a Linux environment Experience with building end-to-end reusable pipelines from data acquisition to model output delivery Quick learner, adaptable, with the ability to work independently in a fast-paced environment Strong oral and written communication skills. Ability to conduct meetings and make professional presentations, and to explain complex concepts and technical material to non-technical users Intuit provides a competitive compensation package with a strong pay for performance rewards approach. This position will 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:
Intuit
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Atlanta, GA