Applied Scientist, Central Machine Learning
Do you want to join an innovative team of scientists who use machine learning and statistical techniques to create state‐of‐the‐art solutions for providing better value to Amazon's customers? Do you want to build and deploy advanced algorithmic systems that help optimize millions of transactions every day? Are you excited by the prospect of analyzing and modeling terabytes of data to solve real‐world problems? Do you like to own end‐to‐end business problems/metrics and directly impact the profitability of the company? Do you like to innovate and simplify? If yes, then you may be a great fit to join the Machine Learning and Data Sciences team for India Consumer Businesses.
If you have an entrepreneurial spirit, know how to deliver, love to work with data, are deeply technical, highly innovative and long for the opportunity to build solutions to challenging problems that directly impact the company's bottom‐line, we want to talk to you.
Major responsibilities
* Use machine learning and analytical techniques to create scalable solutions for business problems
* Analyze and extract relevant information from large amounts of Amazon's historical business data to help automate and optimize key processes
* Design, develop, evaluate and deploy innovative and highly scalable models for predictive learning
* Research and implement novel machine learning and statistical approaches
* Work closely with software engineering teams to drive real‐time model implementations and new feature creations
* Work closely with business owners and operations staff to optimize various business operations
* Establish scalable, efficient, automated processes for large‐scale data analyses, model development, model validation and model implementation
* Mentor other scientists and engineers in the use of ML techniques
A day in the life
You will solve real‐world problems by getting and analyzing large amounts of data, generating insights and opportunities, designing simulations and experiments, and developing statistical and ML models. The team is driven by business needs, which requires collaboration with other scientists, engineers, and product managers across the International Emerging Stores organization. You will prepare written and verbal presentations to share insights to audiences of varying levels of technical sophistication.
About the team
Central Machine Learning team works closely with the IES business and engineering teams in building ML solutions that create an impact for Emerging Marketplaces. This is a great opportunity to leverage your machine learning and data mining skills to create a direct impact on millions of consumers and end users.
Basic Qualifications
* 3+ years of building models for business application experience
* PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience
* Experience in patents or publications at top‐tier peer‐reviewed conferences or journals
* Experience programming in Java, C++, Python or related language
* Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high‐performance computing
Preferred Qualifications
* Experience in data applications using large scale distributed systems (e.g., EMR, Spark, Elasticsearch, Hadoop, Pig, and Hive)
* Proficient in any two of these areas: large language models, NLP (Information retrieval, Machine Translation), Computer Vision, Classification models using Boosting/Bagging or Deep Neural Networks.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you're applying in isn't listed, please contact your Recruiting Partner.
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
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