Staff Data Scientist

Company Overview

Job Overview

The Tech Strategic Programs organization delivers for Intuit and Tech Strategy by transforming and driving how our Technology ecosystem operates to accelerate outcomes for our customers. This small, yet mighty team works with senior leaders and partners across the company. We focus on strategic planning, the operating rhythm, executive narratives, workforce programs and delivering intelligent insights that accelerate execution across the tech portfolio and highest priority business growth areas.

We are looking for a strategic and organized leader with a passion for innovation and data-driven optimization. As a Staff Data Scientist, you will work alongside senior leaders from the Technology organizations to deliver insights that lead to faster decisions, increased execution velocity and predictive actions.

Responsibilities

• Use advanced analytics techniques and predictive analytics in developing insights and analyses
• Develop data capabilities, self-service capabilities, and analytical capabilities to streamline and automate the analytical processes
• Provide recommendations utilizing multiple types of data, business knowledge, and strategic assumptions when data doesn’t exist.
• Develop statistical model/anomaly detection and investigate anomalies to monitor and help prevent the potential risk/issue in business.
• Need strong data storytelling skills, with the ability to construct impactful visualizations, communicate insights, and influence leadership.
• Lead in a proactive and results-oriented manner within an ambiguous fast-paced environment.
• Evaluate tradeoffs in design and apply a decision making framework that leverages the right solution for a given business use case
• Analyze large, complex datasets, create and maintain clean data standards to ensure accuracy of both data and for teams to leverage.
• Prioritize and manage stakeholder expectations, working to develop a joint roadmap, balancing short term critical needs with long term planning and development
• Develop analytical tools and programs to unlock data as an asset
• Effectively and proactively communicate cross-functionally and at a variety of altitudes
• Have proficiency in SQL, data visualization tools (Qlik, Tableau, QuickSight), scripting languages (Python, R) and code deployment, change management and collaboration technologies and frameworks (GIT, Jenkins, CICD).

Qualifications

• Strategic Thinking & Business Acumen
  • Demonstrate ability to turn business strategy into business problems, iteratively self-generate hypothesis using data, validate or disprove hypothesis to create actionable insights and recommendations that inform decision making
  • Understands the business strategy and able to drive business case development independently for multiple initiatives using data and strategic thought leadership
  • Able to develop complex learning plans that account for different outcome-based scenarios and provide thought leadership on alternative paths
  • Able to define metrics at the business segment level (e.g.: TT Live, QB Live) in a Business Unit
  • Combine insights, business acumen and strategic considerations to influence cross-functional leaders (e.g.: Directors+)

• Strategy & Measurement for AI Native Experiences
  • Ideate new AI solutions by connecting industry-wide developments in AI with strategic insights, customer knowledge and domain knowledge.
  • Influence cross-functional team in creating a development plan at the business segment or functional group level in a Business Unit
  • Understands the technical architecture powering AI-native experiences (e.g.: GenOS) and the various technology capabilities (e.g. GenOrchestrator, LLMs, GenStudio).
  • Able to identify implications to data, analysis methods and customer behaviors because of these architectural constructs
  • Develops a learning plan by connecting model performance metrics with customer and business metrics.
  • Able to offer alternative strategies of testing and measuring AI-native experiences that account for safety, risk and ethical considerations

• Inference & Algorithms
  • Ability to manage E2E aspects of a complex analytics model/project build (i.e., scope, requirements gathering/finalizing, stakeholder management, communication, project management) that drives BU decision making.
  • Advanced knowledge of data preparation, analysis and modeling using Generative AI tools, data and programming tools (SQL/Python/R) , and data workflow management (authoring, scheduling and monitoring) tools
  • Advanced knowledge of designing complex web experiments (A/B/n, painted-door, bandits etc.) and measure their impact using descriptive and inferential statistical methods.
  • Drive an iterative experimentation culture by combining quantitative insights, strategic thinking and qualitative learnings that increase learning and success rate.