Staff AI Scientist

Intuit

Confirmed live yesterday Trusted

Quick summary

Work type: On-site
Location: New York, NY
Salary: $209,500–$283,500 / yr
Posted: 148 days ago
Freshness: Confirmed live yesterday
Nearby: 99+ roles within 25 mi

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Salary context

Competitive pay

How this pay compares to similar roles

Similar $225k

This role $246k

$167k most similar roles pay here $301k

This role pays more than 57% of similar roles. Most pay $189,525–$260,450 — the shaded band above. At the midpoint, this role pays about $246k versus about $225k for comparable roles.

Based on 240 similar postings.

Employer

About Intuit

Intuit is a financial software company known for products like TurboTax, QuickBooks, Mint, and Credit Karma, helping consumers and small businesses manage their finances and taxes. Industry: Financial Software & Technology

Intuit currently has 174 open roles on FindRole.

Listed pay typically runs $202,500–$274,000 across 152 roles with salary data.

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At a glance

TL;DR · Staff AI Scientist

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As a Staff AI Scientist on the Intuit AI team, you will join a collaborative group of scientists and engineers to build and deploy machine learning models using analytical algorithms and deep learning approaches. You will lead technical work for a scrum team, designing end-to-end architectures, performing hands-on data analysis, and building featurization and ETL pipelines from data acquisition to delivery. Your role involves applying NLP, Causal-ML, Online Learning, Bayesian Learning, Reinforcement Learning, and Deep Learning to solve real-world problems. You will collaborate with product managers and designers to define success criteria while conducting A/B tests. Required skills include proficiency in Python, Scala, Java, or R, along with SQL, Hive, and SparkSQL. You must be comfortable in a Linux environment and skilled in explainable AI and various optimization paradigms like gradient methods.

Skills

Machine Learning Deep Learning NLP Python Scala Java R SQL SparkSQL Hive Causal-ML Bayesian Learning Reinforcement Learning ETL Linux Explainable AI Scrum Git

What you'll do

Build and deploy machine learning models using analytical algorithms and deep learning approaches.
Perform hands-on data analysis including ETL, data cleaning, and feature engineering for large datasets.
Apply advanced techniques like NLP, Causal-ML, Reinforcement Learning, and Bayesian Learning to real-world problems.
Lead the technical work of a scrum team by designing model solutions and end-to-end architectures.
Define success criteria and align model metrics with business goals in collaboration with stakeholders.
Run A/B tests to measure the impact of models and communicate results to leadership.
Research and integrate new machine learning technologies from academia and industry into products.
Build end-to-end reusable pipelines from initial data acquisition to final model output delivery.

What we're looking for

BS, MS, or PhD in Statistics, Mathematics, Computer Science, Economics, Operations Research, or a related field.
4+ years of industry experience in AI science.
4+ years of hands-on expertise in ML paradigms including Causal-ML, supervised/unsupervised, Online, Bayesian, Reinforcement, or Deep Learning.
Proficiency in NLP techniques, Explainable AI, and various machine learning frameworks.
Proficiency in optimization paradigms such as combinatorial optimization, gradient methods, or Bayesian optimization.
Expertise in programming languages including Python, Scala, Java, and/or R.
Proficiency in SQL, Hive, SparkSQL, and working within a Linux environment.
Experience building end-to-end reusable pipelines from data acquisition to model output delivery.

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