Staff Data Scientist

6 months ago

Toronto, Canada Intuit Full time

**Overview**:
Intuit is looking for innovative and hands-on Staff Data Scientist to join the Intuit AI team.

**What you'll bring**:

- 4+ years of industry experience with data science
- BS, MS or PhD in Statistics, Mathematics, Computer Science, Economics, Operations Research, or equivalent work experience
- 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

**How you will lead**:

- Practices leadership and communication skills to influence teams and to evangelize data 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.

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