Work in Washington Veterans Jobs

Description

Transform analytics at global scale with cutting-edge AI/ML and GenAI - Join the founding team of the Science Center of Excellence at ShipTech Analytics!

Revolutionize transportation analytics worldwide by leveraging the latest AI/ML research and technologies at Amazon ShipTech Analytics (STA). As a Sr. Applied Scientist, you'll spearhead initiatives to tackle critical business challenges, optimizing operations and driving innovation across Amazon's massive transportation network.

• Pioneer the flagship AI-programs, employing traditional ML and GenAI to derive insights and recommendations for crucial metrics like Delivery Estimate Accuracy (DEA)

• Optimize business review processes at scale, directly impacting operations for 100K+ Amazonians worldwide

• Collaborate with top minds in AI/ML, working on complex, high-impact problems in the transportation domain

• Drive innovation and thought leadership in supply chain analytics, shaping the future of Amazon's logistics operations.

We're seeking motivated, multi-talented individuals passionate about pushing the boundaries of AI/ML and GenAI in transportation analytics. Join the founding team of STA's Science Center of Excellence and leave your mark on Amazon's global logistics operations. Apply now for this unique opportunity to transform analytics at an unprecedented scale!

Key job responsibilities

You will work closely with business/operations leaders, product managers, business intelligent engineers, software engineering leadership & senior engineers to build capabilities that transform our transportation analytics. This includes analyzing big data, building end-to-end analytics pipelines, prototype optimization/ML/simulation models, and launch production capabilities. You will have exposure to senior leadership as you communicate results and provide scientific guidance to the business. Your insights will be a key influencer of our product strategy and roadmap and your experimental research will inform our future investment areas.

We are open to hiring candidates to work out of one of the following locations:

Bellevue, WA, USA

Basic Qualifications

• 4+ years of building machine learning models for business application experience

• PhD, or Master's degree and 6+ years of building machine learning models for business application experience

• Experience programming in Java, C++, Python or related language

• Experience with neural deep learning methods and machine learning

Preferred Qualifications

• Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.

• Experience with large scale distributed systems such as Hadoop, Spark etc.

• Experience with popular deep learning frameworks such as MxNet and Tensor Flow.

• Knowledge and practical experience in building large-scale solution in transportation and logistics domain

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.

Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $136,000/year in our lowest geographic market up to $260,000/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.