Lead Data Scientist

Responsibilities:

• Work with cross-functional teams to iteratively design, document, implement, and test streaming-based measurement solutions.
• Play a key role in developing, documenting and presenting new methodologies to both internal stakeholders and clients.
• Gain a deep understanding of Audience Measurement products and methodologies, with a focus on streaming measurement globally.
• Design research plans, manage and analyze complex panel data including developing data pipelines, conducting quality reviews, data editing and other relevant processing steps such as weighting, and imputation.
• Provide thought leadership regarding which solutions may be transferable across countries to meet differing business and client needs.
• Balance cost, quality, and schedule requirements to design solutions.
• Adapt as needed
• Correspond and communicate with internal departments regarding project requirements and schedules. 

Required Qualifications

• Master’s Degree (preferred) in Mathematics, Statistics, Economics, Data Science, Computer Science or related field.
• 5+ years of experience with the following:
• Manipulating, analyzing and interpreting complex data sources to derive methodological recommendations through data analyses
• Programming in Python, PySpark and SQL for data pipeline development used to support analytics
• Experience working in cloud-based environments such as AWS
• Project management including ability to prioritize multiple assignments
• High motivation with demonstrated capacity to work on multiple projects with set deadlines, under pressure.
• Collaborative team player with willingness and desire to work with global cross-functional teams of varying sizes.
• Creative aptitude and ability and desire to explore opportunities for new research innovations.
• Excellent oral and written communication skills required for presenting to and collaborating with groups of diverse backgrounds.
• Desired Qualifications:  Understanding of advertising technologies in the marketplace. Domain expertise in audience measurement Experience in sampling, variance estimation, bias reduction techniques, imputation, and weighting.