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Role Description
We're looking for a Senior/Staff Data Scientist to partner with Marketing, Brand, Product & Finance teams to answer key questions about the effectiveness of marketing across all our paid & owned channels. We solve challenging problems & boost business growth through a deep understanding of user behaviors with applied analytics techniques & business insights. An ideal candidate should have robust knowledge of marketing measurement methods (eg. causal inference, attribution, MMM) & strong technical fluency in scripting(Python/R) & querying(SQL)
Responsibilities
- Evaluate & improve our marketing measurement leveraging techniques such as MMM(Marketing Mix Modeling), MTA(Multi touch attribution) & incrementality testing
- Perform analytical deep-dives to analyze problems & opportunities, identify the hypothesis & design & execute experiments
- Inform future experimentation design & roadmaps by performing exploratory analysis to understand user engagement behavior & derive insights
- Create personalized segmentation strategies leveraging propensity models to enable targeting of offers & experiences based on user attributes
- Identify key trends & build automated reporting & executive-facing dashboards to track the progress of acquisition, monetization, & engagement trends.
- Extract actionable insights through analyzing large, complex, multi-dimensional customer behavior data sets
- Monitor & analyze a high volume of experiments designed to optimize the product for user experience & revenue & promote best practices for multivariate experiments
- Translate complex concepts into implications for the business via excellent communication skills, both verbal & written
- Understand what matters most & prioritize ruthlessly
- Work with cross-functional teams (including Data Science, Marketing, Product, Engineering, Design, User Research, & senior executives) to rapidly execute & iterate
Requirements
- Bachelors or above in quantitative discipline: Statistics, Applied Mathematics, Economics, Computer Science, Engineering, or related field
- 5-8+ years experience using analytics to drive key business decisions; examples include business/product/marketing analytics, business intelligence, strategy consulting
- Proven track record of being able to work independently & proactively engage with business stakeholders with minimal direction
- Significant experience with SQL & large unstructured datasets such as Hadoop
- Deep understanding of statistical analysis, experimentation design, & common analytical techniques like regression, decision trees
- Solid background in running multivariate experiments to optimize a product or revenue flow
- Strong verbal & written communication skills
- Proficiency in programming/scripting & knowledge of statistical packages like R or Python
Preferred Qualifications
- Experience in using open source packages for incrementality tests(e.g. Metas Geolift, Googles Causal Impact) & MMM (Googles Meridian, Lightweight MMM or Metas Robyn)
- Master's or Ph.D. Degree in a quantitative field
- Experience with predictive modeling, machine learning, & experimentation/causal inference methods.
Compensation
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