Lead Data Scientist, Ads (Multiple Positions)

Lead Data Scientist, AdsLocation: San JoseEmployment Type: RegularJob Code: A52681ResponsibilitiesPerform analysis including data gathering and requirements specification, processing, analysis, ongoing deliverables, and presentations.Research applied data science questions in the ads system to improve prediction accuracy, develop data-driven to-to-market strategies, and drive advertiser value.Utilize quantitative analysis and data mining to determine how users interact with ads products, analyzing current performance, and identifying opportunities to improve the system.Develop data structures and metrics, advocating for changes for product development, and mine large amounts of data and extract useful product insights.Define KPIs and develop analytic framework to evaluate on-platform assets engagement and drive continuous UI/UX iterations via A/B testing.Define core metrics, build essential data tracking dashboard, and identify opportunities from the company's database and convert the insights into real changes and new features.Interact cross-functionally, making business recommendations with effective presentations of findings at multiple levels of stakeholders through visual displays of quantitative information.Mentor junior- and mid-level data scientists.QualificationsMust have a Master's degree or foreign equivalent degree in Computer Science, Engineering (any), Data Science, Applied Data Analytics, Statistics, Mathematics, or a related quantitative field, and 3 years of related work experience; or a Bachelor's degree or foreign equivalent degree in Computer Science, Engineering (any), Data Science, Applied Data Analytics, Statistics, Mathematics, or a related quantitative field, and 5 years of post-bachelor's, progressive related work experience.Of the required experience, must have 3 years of experience in each of the following: Leveraging advanced data gathering, processing, and analysis techniques to develop and deliver data-driven recommendations to support and influence business decisions; Using SQL queries and data visualization tools to gather, process, visualize, and analyze large quantities of data to detect trends and anomalies in support of business opportunity identification; Analyzing large quantities of data to detect anomalies using Python and statistical analysis techniques; Providing data-driven insights and recommendations to mitigate insufficiencies models based on model performance, regulations, or business requirements; and Developing and maintaining tables, views, indexes, datasets, or data pipelines to extract, clean, transform, load and maintain data across multiple databases.Travel Requirement: International travel required up to 20%.