Sr. Applied Scientist - Forecasting
Have you noticed how often the weather forecast is wrong? How you ever wondered how forecasts are made to model the complexities of consumer demand and product trends? What if you had the opportunity to analyze forecast data to fix forecasting issues before they are impact customers? On Amazon's Supply Chain Optimization Technologies (SCOT) – Forecasting team, you won't be predicting the weather, but will play a major role forecasting Amazon retail item demand. Accuracy in our forecast translates directly into increased profit for Amazon's Worldwide Retail business. Sound exciting? At Amazon, we pioneer, and this space is no exception.
If you are a strong software engineer with a background in Machine Learning, who is passionate about turning massive amounts of data into actionable insights, then this is the right opportunity for you.
You will work with a team of highly skilled and motivated scientists and engineers, who are building the forecasting models for Amazon. We are building state of the art system by using machine learning, and leveraging Amazon's vast computing resources (AWS) and data. As part of your job, you will deal with large amounts of training data, rapidly prototype new models that meet stringent performance requirements, and perform offline and online testing.
- Research and use of statistical 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 features and processes
- Work closely with scientists and engineering teams to create and deploy new features
- Work closely with stakeholders to optimize various business operations
- Establish scalable, efficient, automated processes for large scale data analyses, model development, validation and implementation.
- Track general business activity and provide clear, compelling management reporting on a regular basis
- 8+ years of experience in software development. Experience building large platform systems.
- 5+ years of practical experience applying ML to solve complex problems;
- Algorithm and model development experience for large-scale applications;
- Skilled with Java, C++, or other programming language, as well as with R, MATLAB, Python or similar scripting language;
- Ability to distill informal customer requirements into problem definitions, dealing with ambiguity and competing objectives
- Bachelor / Masters / PhD in Computer Science (Machine Learning, AI, Statistics, Mathematics, or equivalent);
- Extensive knowledge and practical experience in several of the following areas: machine learning, statistics, deep learning, NLP, recommendation systems, dialogue systems, information retrieval;
- Significant peer reviewed scientific contributions in premier journals and conferences;
- Expert in more than one more major programming languages (C++, Java, or similar) and at least one scripting language (Perl, Python, or similar);
- Proven track record of production achievements, handling gigabyte and terabyte size datasets;
- Strong fundamentals in problem solving, algorithm design and complexity analysis;
- Strong personal interest in learning, researching, and creating new technologies with high customer impact;
- Experience with defining research and development practices in an applied environment;
- Proven track record in technically leading and mentoring scientists;
- Superior verbal and written communication and presentation skills, ability to convey rigorous mathematical concepts and considerations to non-experts.
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