AWS Infrastructure Services owns the design, planning,delivery, and operation of all AWS global infrastructure. In otherwords, we’re the people who keep the cloud running. We support allAWS data centers and all of the servers, storage, networking,power, and cooling equipment that ensure our customers havecontinual access to the innovation they rely on. We work on themost challenging problems, with thousands of variables impactingthe supply chain — and we’re looking for talented people who wantto help. You’ll join a diverse team of software, hardware, andnetwork engineers, supply chain specialists, security experts,operations managers, and other vital roles. You’ll collaborate withpeople across AWS to help us deliver the highest standards forsafety and security while providing seemingly infinite capacity atthe lowest possible cost for our customers. And you’ll experiencean inclusive culture that welcomes bold ideas and empowers you toown them to completion. Do you love problem solving? Are youlooking for real world Supply Chain challenges? Do you have adesire to make a major contribution to the future, in the rapidgrowth environment of Cloud Computing? Amazon Web Services islooking for a highly motivated, Data Scientist to help buildscalable, predictive and prescriptive business analytics solutionsthat supports AWS Supply Chain and Procurement organization. Youwill be part of the Supply Chain Analytics team working with GlobalStakeholders, Data Engineers, Business Intelligence Engineers andBusiness Analysts to achieve our goals. We are seeking aninnovative and technically strong data scientist with a backgroundin optimization, machine learning, and statisticalmodeling/analysis. This role requires a team member to have strongquantitative modeling skills and the ability to applyoptimization/statistical/machine learning methods to complexdecision-making problems, with data coming from various datasources. The candidate should have strong communication skills, beable to work closely with stakeholders and translate data-drivenfindings into actionable insights. The successful candidate will bea self-starter, comfortable with ambiguity, with strong attentionto detail and ability to work in a fast-paced and ever-changingenvironment. Key job responsibilities 1. Demonstrate thoroughtechnical knowledge on feature engineering of massive datasets,effective exploratory data analysis, and model building usingindustry standard time Series Forecasting techniques like ARIMA,ARIMAX, Holt Winter and formulate ensemble model. 2. Proficiency inboth Supervised(Linear/Logistic Regression) and UnSupervisedalgorithms(k means clustering, Principle Component Analysis, MarketBasket analysis). 3. Experience in solving optimization problemslike inventory and network optimization. Should have hands onexperience in Linear Programming. 4. Work closely with internalstakeholders like the business teams, engineering teams and partnerteams and align them with respect to your focus area. 5.Detail-oriented and must have an aptitude for solving unstructuredproblems. You should work in a self-directed environment, own tasksand drive them to completion. 6. Excellent business andcommunication skills to be able to work with business owners todevelop and define key business questions and to build data setsthat answer those questions. 7. Work with distributed machinelearning and statistical algorithms to harness enormous volumes ofdata at scale to serve our customers. About the team DiverseExperiences Amazon values diverse experiences. Even if you do notmeet all of the preferred qualifications and skills listed in thejob description, we encourage candidates to apply. If your careeris just starting, hasn’t followed a traditional path, or includesalternative experiences, don’t let it stop you from applying. WhyAWS Amazon Web Services (AWS) is the world’s most comprehensive andbroadly adopted cloud platform. We pioneered cloud computing andnever stopped innovating — that’s why customers from the mostsuccessful startups to Global 500 companies trust our robust suiteof products and services to power their businesses. Work/LifeBalance We value work-life harmony. Achieving success at workshould never come at the expense of sacrifices at home, which iswhy we strive for flexibility as part of our working culture. Whenwe feel supported in the workplace and at home, there’s nothing wecan’t achieve. Inclusive Team Culture AWS values curiosity andconnection. Our employee-led and company-sponsored affinity groupspromote inclusion and empower our people to take pride in whatmakes us unique. Our inclusion events foster stronger, morecollaborative teams. Our continual innovation is fueled by the boldideas, fresh perspectives, and passionate voices our teams bring toeverything we do. Mentorship and Career Growth We’re continuouslyraising our performance bar as we strive to become Earth’s BestEmployer. That’s why you’ll find endless knowledge-sharing,mentorship and other career-advancing resources here to help youdevelop into a better-rounded professional. BASIC QUALIFICATIONS 1.Masters with 5+ years of experience or Bachelors with 8+ years ofexperience in quantitative field (Computer Science, Mathematics,Machine Learning, AI, Statistics, Operational research orequivalent). 2. Experience in Python, R or another scriptinglanguage; command line / notebook usage. Knowledge and expertisewith Data modelling skills, SQL, MySQL, and Databases (RDBMS,NOSQL). 3. Extensive knowledge and practical experience in severalof the following areas: machine learning, statistics, Optimizationusing Linear Programming. 4. Evidence of using relevant statisticalmeasures such as Hypothesis testing, confidence intervals,significance of error measurements, development and evaluation datasets, etc. in data analysis projects. 5. Excellent written andverbal communication skills for both technical and non-technicalaudiences. PREFERRED QUALIFICATIONS 1. Experience in Python, Perl,or another scripting language. 2. Experience in a ML or datascientist role with a large technology company. 3. Functionalknowledge of AWS platforms such as S3, Glue, Athena, Sagemaker,Lambda, EC2, Batch, Step Function. 4. Experience in creatingpowerful data driven visualizations to describe your ML modelingresults to stakeholders. Our inclusive culture empowers Amazoniansto deliver the best results for our customers. If you have adisability and need a workplace accommodation or adjustment duringthe application and hiring process, including support for theinterview or onboarding process, please visit here for moreinformation. If the country/region you’re applying in isn’t listed,please contact your Recruiting Partner. Amazon is an equalopportunity employer and does not discriminate on the basis ofprotected veteran status, disability, or other legally protectedstatus. #J-18808-Ljbffr
