Sr. Data Scientist - FBA products

Seattle, Washington, USA

Full Time
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Posted 1 month ago

Are you passionate about leveraging your data science skills to make impact at scale? Do you enjoy developing innovative algorithms, optimization and predictive models to generate insights and recommendations that will be used by millions of Amazon selling partners and FBA operation teams to drive customer impact?

Over 2 million Sellers in 10 countries list their products for sale on the Amazon Marketplace. To meet our sellers’ needs, our smart and customer-obsessed employees are constantly innovating and building on new ideas. Fulfillment by Amazon (FBA) is an Amazon service for our sellers. FBA Inbound analytics and data science team partners with FBA inbound product management team to optimize supply chain cost and lead time variability by influencing right trade-offs among cost, speed and FBA supply network capacity.

We are looking for a motivated Data Scientist to build, optimize and productionize cutting edge machine learning models. A successful candidate will have strong quantitative, data mining, statistical modeling, machine learning skills and is comfortable facilitating ideation and working from concept through to execution. The position will partner with Product Management, Engineering, Supply Chain optimization and Finance teams to enhance short term and long term business use cases that leverage a range of data science methodologies to solve complex problems for the global FBA Inbound network.

A qualified candidate must have demonstrated ability to develop and manage medium to large-scale models and methodologies that are statistically grounded but also functional and practical. Must possess strong written and verbal communication skills, proven ability to engage and collaborate with customers to drive improvements. Possess high intellectual curiosity with ability to quickly learn new concepts/frameworks, algorithms and technology.

Key responsibilities of FBA Inbound data scientist include the following:
· Research machine learning algorithms and implement by tailoring to FBA business problems
· Manipulate/mine data from large databases (Redshift, SQL Server) and create automated pipeline for model training data sets
· Collaborate with BI/Data Engineering teams and drive the collection of new data and the refinement of existing data sources to continually improve data quality
· Improve model usability by analyzing customer behavior and by gathering requirements from business owners and other tech teams. Incorporate new data sources and implement creative methodologies to improve model performance
· Help build production grade systems to support decision making with an objective of optimizing the FBA Inbound business goals to improve customer experience and grow the Amazon business
· Create and track accuracy and performance of model predictions/recommendations. Retrain models and research processes optimization
· Foster culture of continuous engineering improvement through mentoring, feedback, and analysis.
· Lead setting up of machine learning infrastructure and processes for team to collaborate and share code at scale

To help describe some of our challenges, we created a short video about Supply Chain Optimization at Amazon - http://bit.ly/amazon-scot

Amazon is an Equal Opportunity-Affirmative Action Employer – Minority / Female / Disability / Veteran / Gender Identity / Sexual Orientation / Age

Basic Qualifications


· Master's degree in Computer Science, Computer or Electrical Engineering, Mathematics, Physics, Statistics, Economics or a related field
· 5+ years of experience producing models and analytics for business applications
· Practical experience in several of the following areas: machine learning, statistics, Linear Programming/Optimization, recommendation systems, dialogue systems, information retrieval, NLP, deep learning
· Functional knowledge of AWS platforms such as S3, Glue, Athena, Sagemaker
· Experience in programming in R, Python, Scala or similar languages and maintaining shared code repositories
· Proficiency with TABLEAU/Quicksight/Superset or other web based interfaces to create graphic-rich customizable plots, charts data maps etc
· Ability to distill informal customer requirements into problem definitions, dealing with ambiguity and competing objectives
· Ability to manage and quantify improvement in customer experience or value for the business resulting from research outcomes
· Superior verbal and written communication skills, ability to convey rigorous mathematical concepts and considerations to non-experts.

Preferred Qualifications


· A PhD in a quantitative field (Computer Science, Mathematics, Machine Learning, AI, Statistics, or equivalent)
· 5+ years of experience producing models and analytics for business applications
· Practical experience in several of the following areas: machine learning, statistics, Linear Programming/Optimization, recommendation systems, dialogue systems, information retrieval, NLP, deep learning
· Functional knowledge of AWS platforms such as S3, Glue, Athena, Sagemaker
· Experience in programming in R, Python, Scala or similar languages and maintaining sharedcode repositories
· Proficiency with TABLEAU/Quicksight/Superset or other web based interfaces to create graphic-rich customizable plots, charts data maps etc
· Ability to distill informal customer requirements into problem definitions, dealing with ambiguity and competing objectives
· Ability to manage and quantify improvement in customer experience or value for the business resulting from research outcomes
· Superior verbal and written communication skills, ability to convey rigorous mathematical concepts and considerations to non-experts.
· Demonstrated industry leadership in the fields of Database and/or Data Warehousing, Data Sciences and Big Data processing.

Job tags: AI AWS Big Data Data Mining Data Warehousing Deep Learning Economics Engineering Finance Machine Learning NLP Python R Redshift Research Scala SQL Tableau