amit gupta Big Data, Applied Machine Learning expert

At Amazon, I built the Consumer Marketing Analytics platform that fully automated ingestion, processing and publishing of consumer data. This platform ingested PB's of data from various data silos, ran thousands of analytics and machine learning workflows on a daily basis and published processed data to various data silos. The data that was produced powered many online and offline components of Amazon website. I can help you advise on your big data initiatives.

I am the co founder of InAppBI which empowers applications with affordable analytics. InAppBI connect to various data sources, allows you to transform data using rich scripting and visualize using a drag and drop or a scripting interface. Prior to starting my own company, I was the development manager of Consumer Marketing Analytics team at Amazon. I was responsible for customer segmentation, analytics around it and interfacing with various business units within Amazon which needed that data to better understand their business.

I will help you better understand what you can do with your data. How you can leverage open source, cloud based solutions to better extract meaning from your data. I can also advice on how to leverage data science and machine learning in order to build models that fit your unique needs. Having worked on the technical side of data heavy products at Amazon and Microsoft Bing Search engine, I can help you pick the right architecture that fits your needs - regardless of whether it is for small, big, batch or streaming data. Having built data teams at Amazon, I also have a good understanding of the skill set of people it takes to build a data infrastructure and machine learning team. I can help you identify these skills as well as help you in interviewing people with this skill set. Also I can help you frame a good job description for data engineer or a data scientist.

At Amazon, I was responsible for automating model building and scoring of 3k+ propensity models and 1k+ for downstream impact analysis at regular cadence. Some of the machine learning models we automated were propensity of purchase by a customer in product category, sub category, by digital marketing channel, by event such as propensity to purchase on Black Friday/Halloween/Cyber Monday etc. Also we build models predicting downstream value of an event such as sign up for Amazon Credit Card or First purchase in a category etc At Microsoft Bing, I build Machine Learning models such as the first version of binary classifier for automatically classifying web queries as commericial/non commercial. I also worked on multiclass classifier for classifying web queries to Bing Shopping product taxonomy and developed algorithms for metadata(brand, model, spec attribute etc) identification within retail queries.