Analyze large, complex datasets to uncover trends, patterns, and actionable insights for Ads platform optimization.
Translate business challenges into data-driven strategies to maximize ad performance and revenue.
Modeling & Machine Learning:
Design, develop, and deploy statistical models, machine learning algorithms, and generative AI solutions for CTR, CVR, demographic inference, and inventory forecasting.
Integrate models into production systems to enable real-time insights and automated decision-making.
Experimentation & Validation:
Develop A/B testing frameworks and experimental designs to validate model improvements and quantify business impact.
Continuously monitor and improve data quality and model performance.
Collaboration & Stakeholder Engagement:
Work closely with Data Engineering, Product, Ad Tech, and Business teams to deploy end-to-end solutions.
Present insights, methodologies, and business impact to both technical and non-technical stakeholders.
Innovation & Technology Adoption:
Stay updated with advancements in data science, machine learning, and AI.
Apply large language models (LLMs) and generative AI techniques for contextual ad targeting and intelligent advertiser tooling.
