The Mailchimp Customer Success (CS) Data Science & Analytics team’s mission is to empower world-class customer experiences across digital and expert-led channels by delivering data-driven insights, experimentation, and predictive intelligence. We partner closely with Customer Success, Product, Data Engineering, and Operations teams to improve customer engagement, retention, and long-term success for Mailchimp’s small and mid-market customers.
As a Staff Data Scientist, you will serve as a senior individual contributor and strategic thought partner, applying deep analytical expertise and business judgment to some of Mailchimp CS’s most complex and high-impact problems. You will shape measurement frameworks, lead advanced experimentation and causal analysis, and translate insights into clear recommendations that influence strategy and execution across the organization.
This role offers a unique opportunity to help define how Customer Success impact is measured at scale—especially as Mailchimp evolves its data platforms, AI-enabled experiences, and customer engagement models.
Responsibilities
Serve as a strategic analytics partner to Customer Success, Product, and Operations leaders—helping define problems, success metrics, and data-informed decisions.
Conceptualize ambiguous business problems, formulate hypotheses, and design rigorous analytical approaches to evaluate Customer Success programs and initiatives.
Design, execute, and interpret experiments beyond traditional A/B testing, including causal inference methods (e.g., quasi-experiments, DiD, matching, synthetic control).
Develop and maintain scalable measurement frameworks for key CS outcomes such as engagement, retention, TNPS, customer health, and support effectiveness.
Build predictive models and durable customer segmentation approaches to improve targeting, prioritization, and customer experience personalization.
Translate complex analyses into clear, actionable insights and narratives for both technical and non-technical stakeholders, including senior leadership.
Partner with Data Engineering to ensure high data quality, well-defined metrics, and scalable analytics assets—especially during platform and data migrations.
Evaluate and help measure the impact of AI/ML- and LLM-driven customer experiences across human and digital success channels.
Champion analytics rigor, experimentation best practices, and reusable solutions that scale impact beyond individual projects.
Role-model Intuit’s “Win Together” mindset by collaborating deeply across teams and elevating the analytical bar of the broader organization.
Qualifications
6+ years of experience in data science, analytics, or product analytics, with demonstrated impact in customer success, product, marketing, or go-to-market domains.
Strong foundation in statistics, experimentation, and causal inference, including experience designing and interpreting analyses beyond simple A/B tests.
Advanced SQL skills and strong proficiency in Python for data analysis, modeling, and experimentation (e.g., pandas, numpy, scikit-learn, statsmodels).
Proven ability to work with large, complex datasets and translate insights into business decisions.
Experience building scalable, reusable analytics or modeling solutions that improve efficiency and consistency.
Excellent communication and storytelling skills, with the ability to influence stakeholders and guide decision-making.
Bachelor’s degree in a quantitative field (Statistics, Economics, Mathematics, Computer Science, Data Science, or related); advanced degree preferred.
Preferred
Experience in fintech, SaaS, marketing technology, or SMB-focused products.
Familiarity with Customer Success metrics and concepts (e.g., customer health, churn risk, lifecycle engagement, support effectiveness).
Experience partnering closely with Product, Engineering, and AI/ML teams.
Familiarity with BI and visualization tools (e.g., Tableau, Qlik, Quicksight).
Experience using version control (git) and applying software engineering best practices to analytics workflows.
Exposure to Generative AI or LLM-powered analytics and customer-facing use cases.
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:
