Staff AI Scientist

Intuit Inc.; Mountain View (CA); On-site; USD 198,000 - 268,000; Full time

Job summary

Join a forward-thinking company as a Staff AI Scientist, where you will leverage your expertise in machine learning and data analysis to create innovative solutions that impact thousands of customers. In this dynamic role, you will lead a collaborative team, driving the development of advanced AI models and ensuring they align with business objectives. You will have the opportunity to work with cutting-edge technologies, conduct A/B tests, and communicate findings to stakeholders. This position offers a competitive compensation package, including bonuses and equity rewards, making it an exciting opportunity for those passionate about AI and its real-world applications.

Qualifications

• 4+ years of experience in AI science and machine learning.
• Proficient in NLP techniques and modern analytical tools.
• Strong communication skills to explain complex concepts.

Responsibilities

• Lead technical work of a scrum team and ensure high-quality code.
• Collaborate with stakeholders to define success criteria.
• Research and enable new ML technologies to solve customer problems.

Skills

Machine Learning

Data Analysis

Natural Language Processing (NLP)

Communication Skills

Statistical Analysis

Problem Solving

Adaptability

Education

BS in Statistics, Mathematics, Computer Science, or equivalent

MS or PhD in relevant field

Tools

Python

Scala

Java

R

SQL

Hive

SparkSQL

Job description

Intuit is looking for an innovative and hands-on 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.

Intuit provides a competitive compensation package with a strong pay for performance rewards approach. The expected base pay range for this position is Bay Area California $198,000 - $268,000. 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 pay equity for employees, Intuit conducts regular comparisons across categories of ethnicity and gender.

Minimum Requirements

• 4+ 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.