Staff Data Scientist

Intuit, Inc.; New York (NY); Presencial; USD 194.000 - 263.000; Jornada completa

Descripción de la vacante

Mailchimp is seeking a Staff Data Scientist to lead analytics for Messaging, guiding product strategy and revenue growth across SMS, WhatsApp, and other channels. You will partner with product, engineering, design, finance, and marketing to translate data into actionable roadmaps.

You will apply advanced analytics, causal inference, and ML to model customer journeys, run experiments, and build scalable data products that democratize insights across teams.

Formación

• 8+ years of experience in Data Science, Product Analytics, or related quantitative field.
• Expertise in analytics, experimentation, and causal inference with actionable outcomes.
• Strong predictive modeling, ML, and customer segmentation skills.

Responsabilidades

• Partner with product and engineering to define data-driven messaging strategy.
• Identify growth opportunities across the messaging journey and quantify impact.
• Design and evaluate A/B tests and quasi-experiments to establish causality.
• Build scalable data products and self-service analytics for teams.
• Communicate insights to leadership and mentor teammates.

Conocimientos

Data science

Experimentation

Causal inference

Predictive modeling

Machine learning

SQL

Python

Cross-functional collaboration

Data storytelling

Communication

Educación

Bachelor's degree

Herramientas

SQL

Python

Descripción del empleo

Mailchimp is a leading marketing automation platform that empowers millions of businesses to grow through powerful, easy-to-use marketing and messaging solutions. As we expand beyond email into omnichannel customer engagement, Messaging is at the forefront of Mailchimp's growth strategy, helping businesses connect with their customers through SMS, WhatsApp, RCS, and other emerging communication channels.

Come join the Mailchimp Product Data Science team as a Staff Data Scientist supporting Messaging, one of our most exciting and strategically important growth areas. We are looking for a creative, business-minded problem solver who is passionate about leveraging data science to unlock customer value, accelerate product innovation, and drive measurable business impact.

As a Staff Data Scientist, you will serve as a senior individual contributor and strategic thought partner to Product, Engineering, Design, Finance, and Product Marketing leaders. You will tackle complex, high-impact business problems across the messaging customer journey—from adoption and engagement to monetization, retention, and revenue growth. Your expertise in advanced analytics, experimentation, causal inference, machine learning, and automation will be instrumental in identifying growth opportunities, shaping product strategy, and influencing investment decisions.

This role offers a unique opportunity to help shape the future of Mailchimp's omnichannel messaging strategy. You will lead strategic research, develop scalable data products and measurement frameworks, and translate complex insights into actionable recommendations that influence product roadmaps and accelerate business outcomes. Beyond individual projects, you will help elevate data science capabilities across teams, break down organizational silos, and establish analytical approaches that scale across the broader Mailchimp ecosystem.

Responsibilities

• Strategic Data Partnership & Influence: Serve as a trusted data science partner to Product, Engineering, Design, Finance, and Product Marketing leaders, shaping Mailchimp's omnichannel messaging strategy across SMS, WhatsApp, RCS, and emerging channels. Influence product roadmaps, investment priorities, and business decisions through data-driven insights.
• Product Strategy & Revenue Growth: Identify, size, and prioritize high-impact growth opportunities across the messaging customer journey, including acquisition, adoption, activation, engagement, monetization, and retention. Translate ambiguous business challenges into rigorous analytical frameworks and actionable recommendations that accelerate customer and revenue growth.
• Advanced Analytics & Causal Inference: Lead complex, end-to-end analytical investigations using advanced statistics, SQL, Python, machine learning, and causal inference. Design and evaluate A/B tests and quasi-experiments (e.g., difference-in-differences, matching, synthetic control) to establish causal relationships, quantify incremental impact, and guide product decisions.
• Measurement Strategy & Experimentation: Develop scalable measurement frameworks and define success metrics to evaluate messaging product performance, customer outcomes, and business impact. Champion experimentation best practices and analytical rigor to enable faster, more confident decision-making.
• Scalable Data Products & AI Innovation: Build reusable analytical frameworks, automated insights, opportunity-sizing tools, and self-service data products that democratize access to insights and scale Data Science impact. Leverage modern AI/ML techniques and AI-assisted tools to accelerate analytical workflows and improve organizational productivity.
• Predictive Modeling & Customer Intelligence: Apply machine learning, predictive modeling, and customer segmentation to uncover behavioral patterns, identify growth opportunities, and optimize messaging adoption, engagement, and customer lifetime value.
• Data Quality & Cross-Functional Collaboration: Partner with Data Engineering and platform teams to improve data instrumentation, quality, reliability, and accessibility. Break down organizational silos by developing consistent metrics, sharing learnings, and scaling analytical solutions across messaging channels and the broader Mailchimp ecosystem.
• Executive Communication & Technical Leadership: Translate complex analytical findings into compelling, actionable narratives for technical and nontechnical stakeholders, including senior leadership. Provide technical thought leadership, mentor peers, and elevate the organization’s standards for data-driven decision-making, experimentation, and innovation.

Qualifications

• 8+ years of experience in Data Science, Product Analytics, or a related quantitative discipline, with a demonstrated track record of driving measurable customer, product, and revenue impact in SaaS, marketing technology, or digital products.
• Deep expertise in advanced analytics, experimentation, and causal inference, including A/B testing and quasi-experimental methods (e.g., difference-in-differences, matching, synthetic control, regression discontinuity). Demonstrated ability to select and apply rigorous methodologies to ambiguous business problems and quantify incremental impact.
• Strong foundation in predictive modeling and machine learning, including customer segmentation, propensity modeling, churn prediction, with experience translating models and insights into actionable product and business decisions.
• Advanced proficiency in SQL and Python (e.g., pandas, NumPy, scikit-learn, statsmodels), with hands-on experience analyzing large, complex datasets, developing statistical models, and building scalable analytical solutions.
• Strong product and business acumen, with experience identifying and sizing growth opportunities, evaluating product performance, and influencing strategies related to customer acquisition, adoption, engagement, monetization, and retention.
• Experience building scalable data products and analytical frameworks, including automated insights, opportunity-sizing tools, and self-service solutions that improve decision-making and extend Data Science impact beyond individual analyses.
• Working fluency with modern AI tools and workflows, including LLM-based coding assistants (e.g., Cursor, Claude) and AI-assisted analytics, with the ability to accelerate analytical development while maintaining high standards for accuracy, reproducibility, and rigor.
• Proven ability to navigate ambiguity and influence cross-functional stakeholders, independently leading complex analytical initiatives and translating insights into strategic recommendations that drive measurable business outcomes.
• Exceptional communication and data storytelling skills, with demonstrated ability to influence senior leadership, communicate complex technical concepts clearly, and drive alignment across Product, Engineering, Design, Finance, and Marketing.
• Bachelor's degree in Statistics, Mathematics, Economics, Computer Science, Data Science, Engineering, or a related quantitative field; advanced degree preferred.

Preferred Qualifications

• Experience in messaging, marketing automation, communications platforms, or omnichannel customer engagement, including SMS, WhatsApp, RCS, or email marketing.
• Experience with SaaS monetization, usage-based pricing, product-led growth, and customer lifecycle optimization.
• Demonstrated technical leadership through mentoring, establishing analytical best practices, and scaling data science capabilities across teams.

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:

Mountain View $194,000 - $262,500