Data Scientist, Supply Chain

Excited by using massive amounts of data to develop Machine Learning (ML) and Deep Learning (DL) models? Want to help set the standard in data science for operations? Want to solve complex problems with science and see your solution implemented in the field, impacting hundreds of thousands employees and dozens of millions customers? Eager to learn from many different enterprise’s use cases of AWS ML and DL? Thrilled to be key part of Amazon, who has been investing in Machine Learning for decades, pioneering and shaping the world’s AI technology?

The problems we solve are real, with tangible customer impact. The work involves working with some of largest global enterprises and help them solve previously unsolved problems with Machine Learning and Artificial Intelligence. We are looking for a passionate and talented Data Scientist who will collaborate with other scientists and engineers to develop computer vision and machine learning methods and algorithms to address real-world customer use-cases. You’ll design and run experiments, research new algorithms, and work closely with talented engineers to put your algorithms and models into practice to help solve our customers’ most challenging problems.

AWS Professional Services is a unique team. We pride ourselves on being customer obsessed and highly focused on the AI enablement of our customers. We obsess over finding effective and scalable ways to solve customers demanding problems. If you thrive in a fast-paced environment, you’ll meet your match with us, as you will be part of a vibe of constant improvement. We don’t like to sit still, which is why we always treat every day like the first day. A day to make more good things happen for our customers. That’s the kind of spirit that drives our success and you could be part of it.

A successful candidate will be a person who enjoys diving deep into data, doing analysis, discovering root causes, and designing long-term solutions. It will be a person who likes to have fun, loves to learn, and wants to innovate in the world of AI.



Responsibilities
They will develop mathematical models for forecasting and optimization, using typically linear/integer programming, machine/deep learning, simulation, forecasting and statistical techniques. In addition to assessment of historical trends, they will require envisaging the impact of various business initiatives and strategy. They may drive customer decisions including site location, design, capacity expansion (buildouts), financial viability and impact on network dynamics. The candidate may significantly contribute in improving customer’s network efficiency by successfully partnering with various operations, consumer, engineering, real estate and finance teams


Forecasting/Planning/Analysis
· Support the capacity expansion within the existing customer warehouse and introduction of new network nodes.
· Carry out sensitivity analysis and create a decision model for optimal utilization of the existing capacity, considering all other business impacts.
· Contribute to the customer’s Operational Planning process.
· Initiate and support the implementation of process-improvements, both the business processes and the technical solutions.
· Partner with the customer Supply Chain teams and contribute on network modeling and optimization, in order to find the best network topology across their geographic region. This includes the location of the warehouses, inventory placement to name a few.
· Support the existing tools and systems in the Customer ecosystem for Sales and Operations Planning (S&OP) and Storage Capacity.


This position can have periods of up to 10% travel.

This position requires that the candidate selected be a U.S. citizen and be willing to maintain a TS security clearance.

Basic Qualifications

· A Masters Degree in a highly quantitative field (Computer Science, Machine Learning, Operational Research, Statistics, Mathematics, etc.) or equivalent experience
· 6+ years of experience working with large-scale, complex datasets to create/optimize machine learning, predictive, forecasting, and/or optimization models
· Ability to write production level code in R or Python
· Knowledge and experience of writing and tuning SQL
· Practical understanding and hands-on experience with the following:
· Supervised learning methods (linear and logistic regression, generalized linear models, decision trees, random forests, support vector machines, graphical models, neural networks / deep learning, etc.).
· Unsupervised learning methods (K-means, hierarchical clustering, association rules, principal components, etc.).
· Mathematical optimization (mixed integer programming, linear programming, stochastic programming/optimization discrete optimization convex optimization, reinforcement learning, etc.).
· Track record of diving into data to discover hidden patterns and solving operational problems with data science
· Past and current experience writing and speaking about complex technical concepts to broad audiences in a simplified format

Preferred Qualifications

· PhD in a highly quantitative field (Computer Science, Machine Learning, Operational Research, Statistics, Mathematics, etc.)
· Experience in building models based on Recurrent Neural Networks (e.g. LSTM) to forecast time series
· 8+ years of industry experience in predictive modeling and analysis
· Good skills with programming languages, such as Java,C/C++, Scala
· Experience with using data visualization tools (e.g. Tableau, Shiny, Django, d3.js)
· Ability to develop experimental and analytic plans for data modeling processes, use of strong baselines, ability to accurately determine cause and effect relations
· Experience with AWS technologies like Redshift, S3, EC2, Data Pipeline, Sagemaker, & EMR
· Combination of deep technical skills and business savvy enough to interface with all levels and disciplines within our organization
· Demonstrable track record of dealing well with ambiguity, prioritizing needs, and delivering results in a dynamic environment

*Inclusive Team Culture*
Here at AWS, we embrace our differences. We are committed to furthering our culture of inclusion. We have ten employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. We have innovative benefit offerings, and we host annual and ongoing learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences. Amazon’s culture of inclusion is reinforced within our 14 Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and earn trust.

*Work/Life Balance*
Our team also puts a high value on work-life balance. Striking a healthy balance between your personal and professional life is crucial to your happiness and success here, which is why we aren’t focused on how many hours you spend at work or online. Instead, we’re happy to offer a flexible schedule so you can have a more productive and well-balanced life—both in and outside of work.

*Mentorship & Career Growth*
Our team is dedicated to supporting new team members. Our team has a broad mix of experience levels and Amazon tenures, and we’re building an environment that celebrates knowledge sharing and mentorship


Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, visit https://www.amazon.jobs/en/disability/us


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