AWS Infrastructure Services (AIS)
AWS Infrastructure Services owns the design, planning, delivery, and operation of all AWS global infrastructure. In other words, we're the people who keep the cloud running. We support all AWS data centers and all of the servers, storage, networking, power, and cooling equipment that ensure our customers have continual access to the innovation they rely on. We work on the most challenging problems, with thousands of variables impacting the supply chain — and we're looking for talented people who want to help.
You'll join a diverse team of software, hardware, and network engineers, supply chain specialists, security experts, operations managers, and other vital roles. You'll collaborate with people across AWS to help us deliver the highest standards for safety and security while providing seemingly infinite capacity at the lowest possible cost for our customers. And you'll experience an inclusive culture that welcomes bold ideas and empowers you to own them to completion.
Do you love problem solving? Are you looking for real world Supply Chain challenges? Do you have a desire to make a major contribution to the future, in the rapid growth environment of Cloud Computing?
Amazon Web Services is looking for a highly motivated Data Scientist to help build scalable, predictive and prescriptive business analytics solutions that supports AWS Supply Chain and Procurement organization. You will be part of the Supply Chain Analytics team working with Global Stakeholders, Data Engineers, Business Intelligence Engineers and Business Analysts to achieve our goals.
We are seeking an innovative and technically strong data scientist with a background in optimization, machine learning, and statistical modeling/analysis. This role requires a team member to have strong quantitative modeling skills and the ability to apply optimization/statistical/machine learning methods to complex decision-making problems, with data coming from various data sources. The candidate should have strong communication skills, be able to work closely with stakeholders and translate data-driven findings into actionable insights. The successful candidate will be a self-starter, comfortable with ambiguity, with strong attention to detail and ability to work in a fast-paced and ever-changing environment.
Key job responsibilitiesDemonstrate thorough technical knowledge on feature engineering of massive datasets, effective exploratory data analysis, and model building using industry standard time Series Forecasting techniques like ARIMA, ARIMAX, Holt Winter and formulate ensemble model.Proficiency in both Supervised (Linear/Logistic Regression) and Unsupervised algorithms (k means clustering, Principle Component Analysis, Market Basket analysis).Experience in solving optimization problems like inventory and network optimization. Should have hands-on experience in Linear Programming.Work closely with internal stakeholders like the business teams, engineering teams and partner teams and align them with respect to your focus area.Detail-oriented and must have an aptitude for solving unstructured problems. You should work in a self-directed environment, own tasks and drive them to completion.Excellent business and communication skills to be able to work with business owners to develop and define key business questions and to build data sets that answer those questions.Work with distributed machine learning and statistical algorithms to harness enormous volumes of data at scale to serve our customers.About the teamAWS values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn't followed a traditional path, or includes alternative experiences, don't let it stop you from applying.
BASIC QUALIFICATIONSMasters with 5+ years of experience or Bachelors with 8+ years of experience in quantitative field (Computer Science, Mathematics, Machine Learning, AI, Statistics, Operational research or equivalent).Experience in Python, R or another scripting language; command line / notebook usage. Knowledge and expertise with Data modelling skills, SQL, MySQL, and Databases (RDBMS, NOSQL).Extensive knowledge and practical experience in several of the following areas: machine learning, statistics, Optimization using Linear Programming.Evidence of using relevant statistical measures such as Hypothesis testing, confidence intervals, significance of error measurements, development and evaluation data sets, etc. in data analysis projects.Excellent written and verbal communication skills for both technical and non-technical audiences.PREFERRED QUALIFICATIONSExperience in Python, Perl, or another scripting language.Experience in a ML or data scientist role with a large technology company.Functional knowledge of AWS platforms such as S3, Glue, Athena, Sagemaker, Lambda, EC2, Batch, Step Function.Experience in creating powerful data driven visualizations to describe your ML modeling results to stakeholders.Posted: September 26, 2024 (Updated 3 days ago)
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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.
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