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Intuit

Tax, accounting, and personal-finance software

Staff AI Scientist

Applied Machine LearningConfirmed live in the last 24 hours
Full-timeNew York, NY, USAIn-person

About the Job

Requirements

  • Four or more years of industry experience in AI science.
  • A BS, MS, or PhD in Statistics, Mathematics, Computer Science, Economics, Operations Research, or equivalent.
  • Four or more years of hands-on expertise in machine-learning paradigms such as causal machine learning, supervised or unsupervised learning, online learning, Bayesian learning, reinforcement learning, or deep learning.
  • Proficiency in optimization paradigms such as combinatorial optimization, gradient methods, or Bayesian optimization.
  • Proficiency in natural language processing techniques, explainable AI, and machine-learning frameworks.
  • Expertise in modern analytical tools and programming languages such as Python, Scala, Java, or R.
  • Proficiency in SQL, Hive, SparkSQL, or similar tools.
  • Comfort working in a Linux environment.
  • Experience building end-to-end reusable pipelines from data acquisition to model-output delivery.
  • Ability to work independently in a fast-paced environment and adapt quickly.
  • Strong oral and written communication skills, including conducting meetings, giving professional presentations, and explaining complex concepts and technical material to non-technical users.

Responsibilities

  • Influence teams and promote AI science across the organization.
  • Collaborate with stakeholders to define success criteria and align model metrics with business goals.
  • Work with product managers, software engineers, and designers to design experiments and minimum viable products.
  • Lead a scrum team's technical work by initiating and designing model solutions, driving end-to-end architecture designs, and holding the team accountable for code quality, Git, design, costs, and implementation standards.
  • Perform hands-on data analysis and modeling with large datasets, including discovering data sources, obtaining data access, cleaning data, and preparing data for modeling; perform ETL and design and build featurization.
  • Apply data mining, natural language processing, and machine-learning methods—including supervised and unsupervised learning, causal machine learning, online learning, Bayesian learning, reinforcement learning, and deep learning—to real-world problems and datasets.
  • Run A/B tests to assess the impact of the team's work and communicate results to peers and leaders.
  • Coordinate with partners to ensure successful delivery and integration of data-science solutions.
  • Research and enable new machine-learning technologies, monitor developments in academia and industry, and consider potential applications to Intuit customer problems.

About the Company

Intuit

Tax, accounting, and personal-finance software

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.

Company size
10,001+
Company stage
IPO
Headquarters
Mountain View, CA
Founded
1983

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