Manager 2, Data Science (GBSG - Mid Market)

Overview

• Lead and develop a team of data scientists supporting Marketing and Sales for Intuit Enterprise Suite (IES), providing coaching, structured feedback, and growth opportunities to strengthen technical skills, business impact, and emerging leadership capabilities.
• Own a well-defined problem space within GTM analytics (e.g., pipeline generation, conversion, or revenue performance), setting clear priorities and ensuring delivery against team goals with measurable business outcomes.
• Build team operating mechanisms and scalable processes that bring clarity, focus, and execution rigor in a fast-paced and evolving mid-market environment.
• Partner with Marketing, Sales, Product, and Finance stakeholders to apply data-driven insights to business problems, influencing decisions within your domain and contributing to broader GTM strategy.
• Translate business needs into clearly scoped analytical problems and roadmaps, and drive end-to-end execution—from problem framing and analysis to insight generation and stakeholder adoption.
• Define and operationalize core metrics and measurement frameworks to track performance across the marketing and sales funnel, ensuring consistency and trust in data-driven decisions.
• Apply and guide the team in using advanced analytics techniques (experimentation, statistical modeling, machine learning) to solve business problems, with a focus on practical impact over theoretical complexity.
• Promote a culture of experimentation and test-and-learn, enabling teams to validate hypotheses and improve performance through data.
• Drive adoption of best practices in data science workflows, tooling, and communication to improve team effectiveness and output quality.
• Demonstrate and foster a “win together” mindset, collaborating effectively across teams while constructively challenging assumpti
  
  

Responsibilities

• Lead and develop a team of data scientists supporting Marketing and Sales for Intuit Enterprise Suite (IES), providing coaching, structured feedback, and growth opportunities to strengthen technical skills, business impact, and emerging leadership capabilities.
• Own a well-defined problem space within GTM analytics (e.g., pipeline generation, conversion, or revenue performance), setting clear priorities and ensuring delivery against team goals with measurable business outcomes.
• Build team operating mechanisms and scalable processes that bring clarity, focus, and execution rigor in a fast-paced and evolving mid-market environment.
• Partner with Marketing, Sales, Product, and Finance stakeholders to apply data-driven insights to business problems, influencing decisions within your domain and contributing to broader GTM strategy.
• Translate business needs into clearly scoped analytical problems and roadmaps, and drive end-to-end execution—from problem framing and analysis to insight generation and stakeholder adoption.
• Define and operationalize core metrics and measurement frameworks to track performance across the marketing and sales funnel, ensuring consistency and trust in data-driven decisions.
• Apply and guide the team in using advanced analytics techniques (experimentation, statistical modeling, machine learning) to solve business problems, with a focus on practical impact over theoretical complexity.
• Promote a culture of experimentation and test-and-learn, enabling teams to validate hypotheses and improve performance through data.
• Drive adoption of best practices in data science workflows, tooling, and communication to improve team effectiveness and output quality.
• Demonstrate and foster a “win together” mindset, collaborating effectively across teams while constructively challenging assumptions and improving ways of working.
  
  

Qualifications

• BS, MS, or PhD in Statistics, Computer Science, Applied Mathematics, Econometrics, Operations Research, or a related quantitative field.
• 8 years of experience in data science, analytics, or a related role, including prior experience leading or mentoring individuals or small teams.
• Demonstrated ability to own and deliver within a defined problem space, with clear examples of driving measurable impact (e.g., improving conversion, pipeline efficiency, or revenue outcomes).
• Strong hands-on proficiency in SQL, Python, R, and experience working with large-scale datasets and visualization tools.
• Solid expertise in at least one core area such as experimentation/causal inference, predictive modeling, or statistical analysis, with the ability to apply methods appropriately to business problems.
• Experience partnering with cross-functional stakeholders (Marketing, Sales, Product, etc.), with the ability to influence decisions through clear communication and data storytelling.
• Proven ability to translate ambiguous business questions into structured analyses, and deliver actionable insights with follow-through.
• Strong balance of execution and emerging strategic thinking—able to connect team work to broader business goals while staying close to the details.
• Comfortable operating in ambiguous, fast-paced environments, with the ability to prioritize effectively and adapt to changing business needs.
  
  

Intuit provides a competitive compensation package with a strong pay for performance rewards approach. This position may be eligible for a cash bonus, equity rewards and benefits, in accordance with our applicable plans and programs (see more about our compensation and benefits at Intuit®: Careers | Benefits). Pay offered is based on factors such as job-related knowledge, skills, experience, and work location. To drive ongoing fair pay for employees, Intuit conducts regular comparisons across categories of ethnicity and gender. The expected base pay range for this position is: