Overview
Mailchimp is the world’s leading marketing automation platform. More than 16 million people and businesses use Mailchimp to design and send 1 billion emails and messages a day. We empower small businesses with a suite of powerful and easy-to-use email and messaging tools that integrate with hundreds of popular applications and services.
Come join the Mailchimp Product Data Science team as a Staff Data Scientist. We are looking for creative problem solvers with a passion to deliver impact through data-driven insights.
As a Staff Data Scientist, you will operate as a senior individual contributor. You will partner closely with peers and leaders to identify, validate, and refine innovative growth strategies. Your expertise in advanced analytics, experimentation, causal inference, machine learning and automation will be instrumental in surfacing critical insights and translating them into actionable hypotheses that will fuel sustained customer and revenue growth.
Responsibilities
- Strategic Data Partnership & Influence: Act as the lead data science partner for Product, Engineering, Design, Marketing, and Finance leaders. Translate complex analytical findings into clear, concise narratives to drive cross-functional alignment and concrete business actions.
- Business Strategy & Analytical Frameworks: Drive product and business strategy by translating complex business challenges into rigorous analytical frameworks. Utilize integrated data from across the business to deliver actionable recommendations that fuel strategic growth.
- Advanced Analytics & Causal Inference: Perform deep, end-to-end analysis using advanced SQL, Machine Learning (ML), and Artificial Intelligence (AI) to generate insights that create tangible customer and business value. Design, execute, and analyze A/B tests and quasi-experiments (e.g., synthetic control, regression discontinuity) to establish causal relationships and precisely measure impact.
- Data Democratization & Insights at Scale: Champion self-serve analytics by creating robust dashboards, visualizations, and tools. Scale access to critical insights across all cross-functional teams and leadership levels.
- Data Infrastructure, Quality & Governance: Partner with data engineering and platform teams to establish reliable, scalable data pipelines and tracking instrumentation. Uphold the highest standards for data hygiene, integrity, and governance.
- Communication & Storytelling: Demonstrate excellent communication and compelling storytelling skills. Simplify highly complex technical and data-driven insights into narratives that resonate with stakeholders at all organizational levels.
Qualifications
- 7+ years of experience in data science, with a proven record of applying advanced analytical methods to drive product and business growth ideally in Saas or financial technology companies serving consumer or SMBs
- Demonstrated proficiency in causal inference techniques, statistical modeling, machine learning, and experimental design
- Advanced skills in SQL, Python, and other analytical tools, with practical experience using data visualization platforms (e.g., Tableau); Experience with data integration and pipeline development is a plus
- M.S. or Ph.D. in a quantitative field (e.g., Statistics, Computer Science, Economics, Mathematics, Operations Research) or equivalent work experience
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:
Bay Area California: $186,500 - $252,000
New York Metropolitan Area: $186,500 - $252,000