The Ad Optimization group in Bangalore has the charter to build data-science focused products and platforms for the worldwide advertising organization in Amazon.
We supply the technology to build a high quality advertising marketplace, optimizing performance for our advertisers and revenue for our publishers.
This technology powers online advertising programs for some of the world's largest websites, including Amazon.com and other prime online properties.
We currently manage various programs in the Advertising Technology space including Robot Detection, Publisher Fraud Detection, Associates Fraud Detection, ContX (Contextual Extraction), Viewability and User Engagement, Publisher Quality, and User Quality.
Computational Advertising is one of the most challenging areas for algorithmic optimization due to the scale of the problem, direct impact on the business, and because of the interplay of multiple areas like machine learning, statistics, data mining, data streams, computational economics and econometrics.
We build advanced and highly scalable algorithms to optimize performance for advertiser, publisher, ad-network and user.
We work on problems in unsupervised learning, robust statistics, natural language processing, image processing and time series analysis.
A Machine Learning Scientist is responsible for solving complex big-data problems in the online advertising space using data mining, machine learning, statistical analysis and computational economics.
An ideal candidate should have strong depth and breadth knowledge in machine learning, data mining and statistics. The candidate should have reasonable programming and design skills to manipulate unstructured and big data and build prototypes that work on massive datasets.
The candidate should be able to apply business knowledge to perform broad data analysis as a precursor to modeling and to provide valuable business intelligence.