Intuit is looking to solve real-world problems and datasets using AI science and machine learning models that directly affect hundreds of thousands of their customers
Requirements
- 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
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
- 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”
- 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
Other
- BS, MS or PhD in Statistics, Mathematics, Computer Science, Economics, Operations Research, or equivalent
- 4+ years of industry experience with AI science
- 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
- Quick learner, adaptable, with the ability to work independently in a fast-paced environment
