Are you looking to work at the forefront of MachineLearning and AI? Would you be excited to apply cutting edgeGenerative AI algorithms to solve real world problems withsignificant impact? The AWS Industries Team at AWS helps AWScustomers implement Generative AI solutions and realizetransformational business opportunities for AWS customers in themost strategic industry verticals. This is a team of datascientists, engineers, and architects working step-by-step withcustomers to build bespoke solutions that harness the power ofgenerative AI. The team helps customers imagine and scope the usecases that will create the greatest value for their businesses,select and train and fine tune the right models, define paths tonavigate technical or business challenges, developproof-of-concepts, and build applications to launch these solutionsat scale. The AWS Industries team provides guidance and implementsbest practices for applying generative AI responsibly and costefficiently. You will work directly with customers and innovate ina fast-paced organization that contributes to game-changingprojects and technologies. You will design and run experiments,research new algorithms, and find new ways of optimizing risk,profitability, and customer experience. In this Data Scientist roleyou will be capable of using GenAI and other techniques to design,evangelize, and implement and scale cutting-edge solutions fornever-before-solved problems. Key job responsibilities 1.Collaborate with AI/ML scientists, engineers, and architects toresearch, design, develop, and evaluate cutting-edge generative AIalgorithms and build ML systems to address real-world challenges.2. Interact with customers directly to understand the businessproblem, help and aid them in implementation of generative AIsolutions, deliver briefing and deep dive sessions to customers andguide customer on adoption patterns and paths to production. 3.Create and deliver best practice recommendations, tutorials, blogposts, publications, sample code, and presentations adapted totechnical, business, and executive stakeholder. 4. Provide customerand market feedback to Product and Engineering teams to help defineproduct direction. About the team Diverse Experiences Amazon valuesdiverse experiences. Even if you do not meet all of the preferredqualifications and skills listed in the job description, weencourage candidates to apply. If your career is just starting,hasn’t followed a traditional path, or includes alternativeexperiences, don’t let it stop you from applying. Why AWS AmazonWeb Services (AWS) is the world’s most comprehensive and broadlyadopted cloud platform. We pioneered cloud computing and neverstopped innovating — that’s why customers from the most successfulstartups to Global 500 companies trust our robust suite of productsand services to power their businesses. Work/Life Balance We valuework-life harmony. Achieving success at work should never come atthe expense of sacrifices at home, which is why we strive forflexibility as part of our working culture. When we feel supportedin the workplace and at home, there’s nothing we can’t achieve inthe cloud. Inclusive Team Culture Here at AWS, it’s in our natureto learn and be curious. Our employee-led affinity groups foster aculture of inclusion that empower us to be proud of ourdifferences. Ongoing events and learning experiences, including ourConversations on Race and Ethnicity (CORE) and AmazeCon (genderdiversity) conferences, inspire us to never stop embracing ouruniqueness. Mentorship and Career Growth We’re continuously raisingour performance bar as we strive to become Earth’s Best Employer.That’s why you’ll find endless knowledge-sharing, mentorship andother career-advancing resources here to help you develop into abetter-rounded professional. Minimum Qualifications 1. 2+ years ofdata scientist experience and 3+ years of data querying languages(e.g. SQL), scripting languages (e.g. Python) orstatistical/mathematical software (e.g. R, SAS, Matlab, etc.)experience. 2. 3+ years of machine learning/statistical modelingdata analysis tools and techniques, and parameters that affecttheir performance experience. 3. Experience applying theoreticalmodels in an applied environment. 4. Bachelor's degree in aquantitative field such as statistics, mathematics, data science,business analytics, economics, finance, engineering, or computerscience. Preferred Qualifications 1. PhD in a quantitative fieldsuch as statistics, mathematics, data science, business analytics,economics, finance, engineering, or computer science. 2. 5+ yearsof machine learning/statistical modeling data analysis tools andtechniques, and parameters that affect their performanceexperience. 3. Hands on experience with deep learning (e.g., CNN,RNN, LSTM, Transformer). 4. Prior experience in training andfine-tuning of Large Language Models (LLMs) and knowledge of AWSplatform and tools. Amazon is an equal opportunities employer. Webelieve passionately that employing a diverse workforce is centralto our success. We make recruiting decisions based on yourexperience and skills. We value your passion to discover, invent,simplify and build. Protecting your privacy and the security ofyour data is a longstanding top priority for Amazon. Please consultour Privacy Notice (https://www.amazon.jobs/en/privacy_page) toknow more about how we collect, use and transfer the personal dataof our candidates. Amazon is committed to a diverse and inclusiveworkplace. Amazon is an equal opportunity employer and does notdiscriminate on the basis of race, national origin, gender, genderidentity, sexual orientation, protected veteran status, disability,age, or other legally protected status. Our inclusive cultureempowers Amazonians to deliver the best results for our customers.If you have a disability and need a workplace accommodation oradjustment during the application and hiring process, includingsupport for the interview or onboarding process, please visithttps://amazon.jobs/content/en/how-we-hire/accommodations for moreinformation. If the country/region you’re applying in isn’t listed,please contact your Recruiting Partner.#J-18808-Ljbffr
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