Data Scientist, Fulfillment AI

Job summary
A fulfillment center can appear to be a chaotic place. With millions of items moving in and out of an area twice as large as your average theme park every day, a quick peek under the roof would reveal a manic scene. You would see associates, machinery, vehicles, robots, and packages flying about at break-neck speeds and accessing a breathtaking number of shelves and bins that store products. In reality, however, this activity is all highly organized and orchestrated by software, with each movement carefully planned and optimized. However, there are times when mistakes occur: products may disappear, reappear in strange places, become damaged, or worse. When that happens, how does a fulfillment center operating at that size, speed, and scale recover gracefully and with minimal cost? How do we ensure that we meet our commitments to our customers and merchants? How do we find a needle in a haystack when we’re constantly shuffling the haystack around? And how do we do it at extreme scale in an environment of constant growth?

The Fulfillment AI team operates at a nexus of machine learning, computer vision, statistics, optimization, and healthy measure of hard-earned expertise in operations to build automated, algorithmic approaches to solving these problems at minimal cost. We create cutting edge software, building automated processes and workflows in the most complex operational problem space in the business world. So what should you expect from this role?

Major responsibilities: As a Data Scientist you will be working in one of the world's largest and most complex data analytics environments. You should have deep expertise in analyzing huge data sets from multiple domains. You should be expert at designing and implementing solutions that use a range of data science methodologies to automate data analysis or to solve complex business problems. You will design metrics for complex systems. You will deep dive ML training data and feature sets to drive improvements. You will partner with Research and Applied Scientists, SDEs, Technical Program Managers, Product Managers, and business leaders to identify solutions to large problems in Amazon Operations.

Your analysis and solution recommendations will drive system optimizations with global impact. You will develop metrics to quantify the benefits of a solution and influence project resources. You will audit metric data and use it to measure system impact and performance.

You will harness massive and diverse data sets to mine actionable insights for senior leaders. You will automate data feeds, validate the data input and analyze trends that lead to cost saving initiatives. In this role, you will own solving problems through deep data review, statistical analyses, and creation of analytic tools usable by others on the team. Your work products will guide our reporting, benchmarking, program optimization, financial planning, and execution strategy.

The ideal candidate is a motivated self-starter who can thrive in a fast-paced environment. They will enjoy working in a multidisciplinary team of engineers, scientists and business leaders. They will seek to understand processes behind data so their recommendations are grounded.

Flexibility
It isn’t about which hours you spend at home or at work; it’s about the flow you establish that brings energy to both parts of your life. We offer flexibility and encourage you to find your own balance between your work and personal lives.

Mentorship & Career Growth
We care about your career growth too. Whether your goals are to explore new technologies, take on bigger opportunities, or get to the next level, we'll help you get there. Our business is growing fast and our people will grow with it.

Basic Qualifications

· Bachelor's Degree
· 3+ years of experience with data scripting languages (e.g SQL, Python, R etc.) or statistical/mathematical software (e.g. R, SAS, or Matlab)
· 2 years working as a Data Scientist

• Experienced in handling large data sets using SQL and databases in a business environment.

Preferred Qualifications

• MS in Statistics, Applied Math, Operations Research, Economics, or a related quantitative field
• Ability to present technical results to less technical audience including written narratives.
• Proficient with using scripting language such as R, Python, and data manipulation/analysis libraries such as Scikit-learn and Pandas for analyzing and modeling data.
• Experienced in using multiple data science methodologies to solve complex business problems.


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, please visit https://www.amazon.jobs/en/disability/us.