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Intuit Senior Data Scientist United States, California, Mountain View 281801449
05.09.2025
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Responsibilities
- Partner with teams across all of Intuit (including product development, marketing, data engineering, compliance, risk policy, etc.) to enable decision support and key customer insights
- Develop compelling visualizations that crystallize business opportunities for business stakeholders and leaders to make timely decisions.
- Design and run data driven tests and experiments that identify business opportunities and compare performance against company goals.
- Collaborate with stakeholders and analysts to ensure analytical solutions are scalable, repeatable, effective, sustainable, and meet expectations of various stakeholders
- Provide recommendations utilizing multiple types of data, business knowledge, and strategic assumptions when data doesn’t exist.
- Build relationships with other functions critical to the team's mission.
- Mentor and coach other analytics team members to drive creative ideas, use of the latest data techniques and elevate outcomes.
- Deliver key metrics, dashboards and ad-hoc analyses with interpretation, contributing to the development of hypotheses and actions for run the business metrics.
- Designs and implements technical and business documentation
Qualifications
- 4+ Years of Advanced SQL skills to get the data you need from a data warehouse (e.g., Redshift, Hive, SparkSQL, Athena) and perform data segmentation and aggregation from scratch.
- Experience in modern advanced analytical tools and programming languages such as Python.
- Data query and data processing tools/systems (e.g., relational, NoSQL, stream processing).
- Distributed computing systems and related technologies (e.g., Spark, Hive)
- Software engineering fundamentals: version control systems (i.e. Git, Github) and workflows, and ability to write production-ready code.
- Bachelor's Degree in Statistics, Economics, Mathematics, Data Analytics, Finance, Advanced Analytics, or related field. Master's Degree preferred.
- Experience in developing data models, schema design, and working knowledge of cloud computing/services particularly in AWS
- Experience in building multidimensional schemas for consolidating data from multiple sources (Redshift, Hive, SparkSQL, Athena)
- Good working experience with data analytics and visualization tools (Tableau, QlikSense).
- Knowledge of Computer science fundamentals: data structures, algorithms, and performance complexity
- Familiarity with Data Science workflow and life cycle
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