About the role

Manager of Data Science optimizing ad ranking and auction dynamics at Snap Inc. Leading high-performing data science team for actionable insights and analytics in ads.

Responsibilities

Lead a team of data scientists focused on optimizing ad ranking, auction dynamics, and marketplace efficiency to maximize advertiser value and Snapchatter experience
Help build and manage a team of high performing data scientists and help them execute along the most important priorities and deliver world-class products
Establishes a positive, mutually supporting, inclusive and fun team environment where every employee can do their best
Work cross-functionally and partner with product managers, engineers, and researchers to to develop data-driven strategies that shape product direction
Conduct in-depth analysis of all data sources, asking the right questions, testing hypotheses, identifying patterns and providing the necessary business context to translate what it all means
Deliver on data science and analytics roadmap including continuous improvement, accurate and timely reporting and measurement
Define and drive the data science roadmap for ad ranking, including model development, experimentation, actionable insights and measurement framework
Build scalable methodologies for experimentation and causal inference to assess the impact of ranking changes and new product features
Translate complex technical findings into actionable insights and strategic recommendations for leadership and cross-functional stakeholders
Provide strategic direction, project clarity, methodological consultation and deliver results both individually and through managing a high performing team

Experience leading ads data science teams with an in-depth understanding of auction dynamics, pricing, ranking, pacing and ad load
Understanding of statistical analysis, experience with packages, such as R, MATLAB, Stata, etc.
Working knowledge of predictive modeling, machine learning, and experimentation/ causal inference methods
Expertise in the data workflow and pipeline and lead a team responsible for data capture, measurement, and optimization capability management
Expertise in SQL and familiarity with Python
Minimum Requirements BS/BA degree in statistics, mathematics, economics, computer science, engineering or related field or equivalent years of experience
7+ years of post-Bachelor’s quantitative analysis and data science experience; or a Master’s degree in a technical field + 6+ years of post-grad quantitative analysis and data science experience; or a PhD in a relevant technical field + 3+ years of post-grad quantitative analysis and data science experience
3+ years experience in a leadership role within a data organization