Intuit

Job Overview

We are looking for an experienced and highly-motivated Sr. Manager of Data Science to join our Marketing Analytics team. You will lead a team responsible for developing and utilizing data to drive insights and decisions for our Marketing function.

The ideal candidate must have a strong background in data science, inference, automation and experimentation, be able to communicate effectively with stakeholders, and have a passion for driving data-informed solutions.

Responsibilities

• Build and lead a team of analysts and data scientists, providing leadership, direction, and guidance.
• Develop data-driven insights to drive marketing decisions and improve business outcomes.
• Utilize models and develop advanced experimentation methods, such as synthetic controls, propensity score matching techniques etc. to measure marketing's impact across our suite of products.
• Utilize time-series forecasting models to predict growth and set the right growth goals, and develop frameworks to implement marketing attribution models.
• Design, launch, and analyze experiments to understand the incrementality of different messaging and creative campaigns.
• Design measurement approach and identify flaws in experiment practices and results, especially in 3P environments
• Collaborate with marketing, product, and engineering teams to identify insights and guide new campaign and growth roadmaps.
• Manage data integration and engineering with marketing technology platforms for data hygiene, segmentation, and targeting.
• Manage operational effectiveness of the data mining, statistical analysis, and predictive modeling programming activities.
• Partner with cross-functional teams to initiate, lead, or contribute to large-scale/complex strategic projects
• Act as a thought partner to senior leaders to prioritize/scope projects, provide recommendations, and evangelize data-driven business decisions in support of strategic goals.
• Provide technical guidance and mentorship to junior team members on solution design as well as lead code/design reviews.
• Optimize our marketing efforts to make sure our marketing spend has the best possible ROI.
• Apply expertise in data mining and data presentation, as well as knowledge of marketing channels and platforms, to identify opportunities.
• Partner closely with all marketing teams to make critical decisions about where we invest our marketing efforts, understanding the impact of our business, defining key success metrics, and core segmentations.
• Influence team's roadmap by sharing findings with the rest of the company, and driving and verifying change in our marketing channel spend.

Qualifications

• Bachelor's or Master's degree in Statistics, Mathematics, Computer Science, or related field.
• MS in a quantitative field such as computer science, statistics, economics, math, or equivalent work experience + BS
• 3+ years of combined post-graduate academic and industry experience applying scientific methods to solve real-world problems on web-scale data.
• Strong background in statistical analysis, programming, and experimentation.
• Proven ability to apply scientific methods to solve real-world problems on web-scale data.
• Expertise in at least one scripting language (ideally Python/R), with experience building models in either language
• Proficiency in SQL and Hive.
• Strong business and product sense: delight in shaping vague questions into well-defined analyses and success metrics that drive business decisions.
• Excellent communication skills: able to lead initiatives across multiple product areas and communicate findings with leadership and product teams.
• Experience leading key technical projects and substantially influencing the scope and output of others.
• Experience in querying and manipulating large data sets.
• Knowledge to translate quantitative findings into actionable insights and influence business decisions.
• Meaningful time as a data scientist partnering with business functions, ideally with paid marketing teams, and having expertise in analyzing brand campaigns.
• Ability to draw on experience to identify where data can have the most impact and clearly communicate findings and recommendations to partner teams.
• Ability to turn ambiguous questions and problems into clear deliverables and insights.
• Ability to make tradeoffs between speed and accuracy wisely