Applied Scientist III
Compensation: $135,240.00 - $200,710.00 /year *
Employment Type: Full-Time
Industry: Scientific Research
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We are looking for an outstanding Applied Scientist who is interested in shaping the future of how our customers shop for replenishable products on Amazon. The Subscribe & Save and Replenishment Services team owns the technology platform that support recurring delivery programs like Subscribe & Save and a strategic group focused on creating foundational building blocks to make it easier for customers to shop for replenishable products on and off our site, either through one of our replenishment programs (Subscribe & Save, Pantry, Fresh, Whole Foods, Go, etc) or through our core shopping experience.
This Applied Scientist will be responsible for building Machine Learning models that will drive various customer facing scenarios like replenishable product recommendations, replenishable selection management and customer targeting for acquisition and engagement. In partnership with other scientists and engineers, this Applied Scientist will be at the cutting edge of new models and services that will help our customers order and reorder their everyday needs.
The ideal candidate will possess a strong analytical background, an insatiable curiosity, the ability to operate independently and autonomously, strong breadth of ML techniques, experience building large scale Machine Learning models and a passion for working with the data. This Applied Scientist will work closely with engineering and product team. Example problems that this Applied Scientist might look into are: 1) Who are the customers that we want to target with coupons and what are the replenishable products that we want to recommend? 2) Moving beyond the traditional classifications of an ASIN, how can we recognize the types of products that are likely to be reordered? 3) How can we predict what products in the catalog are 'reliable' and are unlikely to go out of stock or have a price change? 4) How can we create a generalized knowledge base of when a product should be reordered? ...and much more!
It's very much Day 1 when it comes to Machine Learning in the world of shopping replenishables online and on Amazon. Come join us in having fun and making history.
1. MS in Computer Science, Machine Learning, Operational Research, Statistics or a related quantitative field 2. 4+ years of hands-on experience in predictive modeling and analysis 3. 3+ years hands-on experience programming in R, Python, Java or other similar programming languages 4. Proficiency in model development, model validation and model implementation for large-scale applications 5. Excellent verbal and written communication skills with the ability to effectively advocate technical solutions to business audiences and engineering teams.
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* The salary listed in the header is an estimate based on salary data for similar jobs in the same area. Salary or compensation data found in the job description is accurate.
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