Key job responsibilities
Use advanced statistical and machine learning techniques to extract insights from large-scale streaming, ad delivery, and auction data sets.
- Design and implement end-to-end data science workflows from data acquisition and cleaning through model development, offline evaluation, A/B testing, and production deployment in partnership with product and engineering teams
- Build, validate, and maintain the statistical models that support the roadmap including Supply tier classification and Supply Quality Index, ad tolerance and fatigue scoring, and propensity and disengagement prediction
- Partner with product and economist teams to design hold out experiments to measure impact of Ad load on revenue and customer engagement; define north star metrics, power calculations, holdout structures, and promotion gates for every major lever.
- Support scalable, self-service analytics by building curated datasets for PVa product, ops, sales, and science covering supply, yield, CX, and advertiser diversification outcomes.
- Partner with product stakeholders and science peers to identify strategic, data-driven opportunities to improve the customer experience and advertiser results.
- Communicate findings, conclusions, and recommendations to technical and non-technical stakeholders
- Stay up-to-date on the latest data science tools, techniques, and best practices and help evangelize them across the organizatio
BASIC QUALIFICATIONS
- 5+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
- 4+ years of data scientist experience
- Experience with statistical models e.g. multinomial logistic regression
PREFERRED QUALIFICATIONS
- 2+ years of data visualization using AWS QuickSight, Tableau, R Shiny, etc. experience
- Experience managing data pipelines
- Experience as a leader and mentor on a data science team