Staff Data Scientist Mailchimp

Intuit

Intuit is looking for a Staff Data Scientist to join the Web Analytics team and drive strategic data initiatives at Mailchimp. The role involves using advanced analytical tools to understand customer behavior, predict outcomes, and enhance Mailchimp's conversion funnel. Collaborating with various departments, the aim is to provide insights that shape future business strategies.

In this role you can expect to have the responsibilities:

• Develop detailed experimentation plans to evaluate the effects of website changes and inform strategic decisions.
• Coordinate data infrastructure efforts to ensure proper data tracking for quality analytics.
• Analyze customer behavior data to derive insights and recommendations that align with strategic goals.
• Profile customer segments to customize the website experience.
• Assess the impact of pricing and promotional changes on customer acquisition over different time frames.
• Create frameworks for understanding customer journey and engagement.
• Calculate the cascading effects of significant customer actions within Mailchimp and Intuit.
• Advise analysts and researchers in designing and executing diverse research studies.
• Develop analytical tools to aid decision-making for leadership.
• Implement statistical inference methods to evaluate web initiative impacts.
• Design dashboards for web decision support.
• Communicate findings through narratives and presentations to stakeholders.

This role requires you to have:

• 5-7 years of analytics experience in a tech company.
• Proficiency in web analytics and event tracking, with a preference for Google Analytics.
• Experience in deploying website experiments with multiple optimization methods.
• Expertise in SQL and Python/R.
• Proficiency in statistical methods and data visualization tools like Tableau.
• Ability to analyze diverse data sources for actionable insights.
• Experience with cloud-based data warehouses such as Google BigQuery.

You would benefit from having:

• Mentorship experience in User Experience Research.
• Experience with distributed computing.
• Knowledge of Causal Inference methodologies.