Staff Data Scientist, CRM & Lifecycle Marketing

Staff Data Scientist role on Intuit’s TurboTax CRM and Lifecycle Marketing data science team, focused on moving from campaign optimization to customer journey design.

Responsibilities

• Shape Lifecycle Marketing strategy using data, including framing the right question before analysis is requested
• Convert ambiguous marketing and product challenges into analytical frameworks, metric trees, and testable hypotheses that influence the CRM roadmap and resourcing
• Partner with Tax leadership and Lifecycle Marketing to define north-star metrics, align on learning plans, and define success across the customer journey stages (re-engagement, start through completion, attach, and return the following year)
• Apply causal measurement and counterfactual reasoning to identify what truly moved key outcomes, including campaign incrementality, journey-level lift, channel mix, halo, and retention
• Design and run experiments, quasi-experiments, holdouts, and synthetic tests when clean A/B testing is not available
• Act as a strategic data science partner across Marketing, Product, Data Engineering, Finance, and adjacent growth teams (paid acquisition, Credit Karma, in-product messaging)
• Translate complex findings into actionable recommendations for Director- and VP-level stakeholders, and drive execution through the appropriate decision channel (Slack, readout, model, or working session)
• Deliver insights at scale through analyses on journeys, audience segments, funnel and cohort performance, and lifetime value to pinpoint where CRM has the most leverage
• Design segmentation and personalization approaches to improve targeting, reduce wasted volume, and free messaging capacity for high-value journeys
• Build dashboards, visualizations, and self-serve tools, including GenAI-powered applications, enabling faster action from marketing and leadership
• Identify, size, and prioritize AI use cases for CRM (personalization, journey orchestration, insight generation) based on business value, using evaluation frameworks to certify non-deterministic experiences (golden datasets, LLM-as-judge with human review, synthetic tests)
• Create and maintain data products used by the business area and its agents, including prototyping data models, pipelines, and surfaces, then partnering with engineering to harden production-ready solutions
• Automate recurring analytical bottlenecks into trusted agentic systems that stakeholders can run independently, with encoded business logic, monitoring, and clear guidance on what can run without a human in the loop
• Champion data hygiene, instrumentation, and decision governance for CRM reporting and campaign measurement

Requirements

• 8+ years of experience in data science and analytics, with demonstrated ability to drive strategy and impact across a business area (CRM, lifecycle marketing, growth, retention, or equivalent); consumer subscription, fintech, or large-scale owned-channel marketing experience strongly preferred
• Track record of first-principles thinking to translate ambiguous business strategy into analytical problems, including framing the question prior to analysis
• Proven ability to design and interpret complex experiments beyond traditional A/B testing, and apply causal inference when experimentation is constrained (holdouts, quasi-experiments, incrementality; MMM or multi-touch attribution used as inputs, not substitutes, for causal claims)
• Deep expertise in causal inference, customer segmentation, journey analytics, and experimentation design, with judgment to balance statistical rigor and business considerations
• Experience building and owning predictive models through their lifecycle (classification, regression, propensity, or similar), accountable for decisions informed by the models
• Experience creating reusable frameworks, methodologies, and data products that are adopted across the broader analytics and marketing community
• Fluency in SQL and a statistical programming language (Python or R); experience partnering with engineering to harden pipelines, instrumentation, and production data products
• Exceptional communication and stakeholder influence, including the ability to influence Director- and VP-level leaders across business and technical teams
• Ability to operate effectively in a fast-paced, seasonal business with minimal guidance, making fast data-driven decisions across one-way vs. two-way door situations
• Ability to use AI-native tools to plan, implement, and synthesize analyses across experiment readouts, quasi-experimental methods, revenue and retention deep dives, and measurement of journey or campaign launches
• Comfort sizing AI use cases and evaluating non-deterministic systems, not limited to using AI for personal productivity
• BS or MS in Statistics, Mathematics, Operations Research, Computer Science, Engineering, Econometrics, or a related field (advanced degree preferred)

Technologies

• SQL
• Python
• R
• GenAI
• LLM-as-judge
• A/B testing
• MMM
• Multi-touch attribution

Compensation

• Salary: USD 194,000 - 262,500 per year

Benefits

• 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, per applicable plans and programs

Location

• Mountain View, CA (onsite)

Nice to Have

• Hands-on experience with CRM platforms (e.g., Braze) and owned-channel measurement (email, push, SMS, in-app)
• Experience designing journey-level measurement (behavioral milestones, coordinated intent) alongside campaign-level operational metrics
• Familiarity with marketing mix models and multi-touch attribution, including when not to treat them as causal evidence