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SeniorFull-timePythonMachine LearningData ScienceData
Salary Range
$68,234 - $92,316 /year
This salary is estimated based on similar roles. The actual salary may vary.
About the Role
We are looking for a Data Scientist to partner with Marketing, Brand, Product, and Finance teams to analyze the effectiveness of marketing across all paid and owned channels. This role focuses on solving challenging problems and boosting business growth through applied analytics techniques and business insights.
Key Responsibilities
- →Evaluate and improve marketing measurement using techniques such as Marketing Mix Modeling (MMM), Multi touch attribution (MTA), and incrementality testing
- →Perform analytical deep-dives to analyze problems and opportunities, identify hypotheses, and design and execute experiments
- →Inform future experimentation design and roadmaps by performing exploratory analysis to understand user engagement behavior
- →Create personalized segmentation strategies using propensity models to enable targeting of offers and experiences
- →Identify key trends and build automated reporting and executive-facing dashboards to track acquisition, monetization, and engagement trends
- →Extract actionable insights through analyzing large, complex customer behavior datasets
- →Monitor and analyze a high volume of experiments to optimize the product for user experience and revenue
- →Translate complex concepts into business implications via excellent communication skills
- →Work with cross-functional teams to rapidly execute and iterate
Requirements
- ✓Bachelor's or above in quantitative discipline: Statistics, Applied Mathematics, Economics, Computer Science, Engineering, or related field
- ✓7+ years experience using analytics to drive key business decisions
- ✓Proven track record of working independently and engaging with business stakeholders
- ✓Significant experience with SQL and large unstructured datasets such as Hadoop
- ✓Deep understanding of statistical analysis, experimentation design, and analytical techniques like regression and decision trees
- ✓Solid background in running multivariate experiments to optimize a product or revenue flow
- ✓Strong verbal and written communication skills
- ✓Proficiency in programming/scripting and knowledge of statistical packages like R or Python
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