Manager 2, Data Analytics

3 days ago

San Diego, United States Intuit Full time

We are looking for an experienced and highly-motivated Manager of Analytics 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. 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 langugage 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

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