We develop scalable and robust state-of-the-art data/analytics/ML and automation solutions that involve learning from different data sources and advanced descriptive, diagnostic, predictive prescriptive and cognitive models. With better forecasts, we drive down supply chain costs, enabling the offer of lower prices and better in-stock selection for our customers.
In this role, you will have an opportunity to both develop advanced scientific solutions, and drive critical customer and business impact. You will play a key role to drive end-to-end solutions from understanding our business requirements, exploring a large amount of historical data and ML models, building prototypes and exploring conceptually new solutions, to working with partner teams for prod deployment. You will collaborate closely with scientists, engineering peers as well as business stakeholders. You will be at the heart of a growing and exciting focus area for Amazon Devices and Services.
We are looking for an individual with outstanding analytical abilities, excellent communication skills, and someone who is comfortable working with cross-functional teams and systems. You will be responsible for researching, prototyping, experimenting, analyzing predictive models and developing smart automation solutions.
Key job responsibilities
· Research and develop new methodologies for demand forecasting, alarms, alerts and automation with advanced models and methods.
· Build and maintain codebase, upholding engineering best practices
· Improve upon existing methodologies by adding new data sources and implementing model enhancements.
· Drive scalable and hands-off-the-wheel solutions.
· Create and track accuracy and performance metrics (both technical and business metrics).
· Create, enhance, and maintain technical documentation, and present to other scientists, engineers and business leaders.
· Drive best practices on the team; mentor and guide junior members to achieve their career growth potential.
About the team
The team is a focused science team with Data and Applied Scientists looking for help with validating the technical decisions we are making and figuring out how to best solve our internal and partner’s needs. We have access to a growing science community within the org and partner with Engineering role on a daily basis.
BASIC QUALIFICATIONS
- 3+ years of building models for business application experience
- PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience
- Experience programming in Java, C++, Python or related language
- Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing
PREFERRED QUALIFICATIONS
- Experience using Unix/Linux
- Experience in professional software development
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 $222,200/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.