Manager 2 Data Science

2 weeks ago

Toronto, Canada Intuit Full time

**Overview**:
Intuit is seeking a Manager, Data Science to join Intuit AI team.

**What you'll bring**:

- BS, MS, or PhD in an appropriate technology field (Computer Science, Statistics, Applied Math, Econometrics, Operations Research, Physics, etc.) or equivalent work experience
- 2+ plus years experience as an established technical leader/Manager of data science teams that have successfully delivered data-driven software products.
- Innovative and disruptive technology leader solving long term strategic outcomes
- Expert command of AI and machine learning, statistical modeling, state-of-the-art tools, and engineering best practices
- Experience in leading teams who have expertise in data mining algorithms and statistical modeling techniques such as clustering, classification, regression, decision trees, neural nets, support vector machines, genetic algorithms, anomaly detection, recommender systems, and natural language processing.
- Impeccable attention to detail and strong ability to convert complex data into insights and action plans
- Strategic thinker, flexible problem solver, great listener and team orientation
- Able to effectively communicate a vision and inspire others to innovate

**How you will lead**:

- Lead and create a team of data scientists
- Mentor and hire the best data scientists in the valley
- Applies artificial intelligence and machine learning techniques to solve complex questions or fuel new business opportunities
- Delivers breakthrough benefits to Intuit users/customers across small business & consumer products using individual, enriched, and aggregated data
- Provides leadership in advanced engineering, data science and analytics in the development of current or future products or technologies
- Provides technical leadership across multiple teams, by understanding a key technology space deeply enough to help guide strategy
- Provide/inspire data science innovations that fuel the growth of Intuit as a whole
- Understands and teaches proven methods and hacking skills in working with divergent data types at scale, to explore and extrapolate data-driven insights using advanced, predictive statistical modeling and testing applied to data acquired and cleansed from a range of sources
- Provides to business stakeholders the entrepreneurial guidance essential for appropriately interpreting and building on findings, and fully exploiting the insights revealed through the research

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