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Sr Data Scientist, WWSO Bedrock

Amazon
  • Seattle, WA
    30+ days ago

    Job Description

    Description Are you passionate about Generative AI? Do you want to help define the future of Go to Market (GTM) at AWS using generative AI? In this role, you will help our customers build and deploy GenAI enabled applications using Amazon Bedrock, customize Generative AI models, and help enterprise customers leverage these models to power end applications. You will engage with product owners to influence product direction and help our customers tap into new markets by utilizing GenAI along with AWS Services. The Worldwide Specialist Organization (WWSO) is part of AWS Sales, Marketing, and Global Services (SMGS), which is responsible for driving revenue, adoption, and growth from the largest and fastest growing small- and mid-market accounts to enterprise-level customers including public sector. We work backwards from our customer's most complex and business critical problems to build and execute go-to-market plans that turn AWS ideas into multi-billion-dollar businesses. WWSO teams include business development, specialist and technical solutions architecture. As part of WWSO, you'll provide expertise across the entire life cycle of an AWS customer initiative, from developing ideas for new services to accelerating the adoption of established businesses. We pride ourselves on thinking big, delivering exceptional results for our customers, and working across AWS as #OneTeam The Generative AI Worldwide Specialist team guides AWS customers on building enterprise-grade GenAI systems. This role will support development of techniques, solutions and architectural blueprints that our customers can use to build their own enterprise-wide Generative AI and Agentic systems in a responsible way, helping them balance democratization of access to GenAI and speed of innovation with following best practices around trustworthy AI, cost efficiency, security, etc. This role specifically will be owning development of best practices around Responsible AI covering such important topics as guardrails, veracity, model evaluations, automated reasoning, fairness, explainability, etc. The role with partner with others on the team to develop comprehensive guidance for AWS GenAI customers using Amazon Bedrock. The deliverables include: helping customers solve complex problems with data science, contributions to the joint technical guidance, architectural blueprints / whitepapers, feedback to AWS Bedrock science teams, thought leadership in the form of public writing and speaking, as well as internal enablement. The role has a global remit. Key job responsibilities - Customer Advisor- Implement, and deploy state of the art machine learning algorithms under Gen AI. You will build prototypes, troubleshoot customer issues, and explore new solutions. You will interact closely with our customers and with the academic community. - Thought Leadership - Evangelize AWS features relating to Responsible AI and share best practices through forums such as AWS blogs, white-papers, reference architectures and public-speaking events such as AWS Summit, AWS re:Invent, etc. - Partner with SAs, Sales, Business Development and the AI/ML Service teams to accelerate customer adoption and providing guidance on their customer engagements. - Develop and support an AWS internal community of ML related subject matter experts worldwide. Create field enablement materials for the broader SA population, to help them understand how to integrate Amazon Web Services GenAI solutions into customer architectures. Basic Qualifications - 5+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience - 4+ years of data scientist experience - Experience with statistical models e.g. multinomial logistic regression - 5+ years of management of technical, enterprise customer facing resources or equivalent experience - 7+ years design/implementation/consulting experience of distributed applications - 5+ years of hands-on experience with AI/ML or related technology domain - 3+ years of hands-on experience with Responsible AI Preferred Qualifications - 2+ years of data visualization using AWS QuickSight, Tableau, R Shiny, etc. experience - Experience managing data pipelines - Experience as a leader and mentor on a data science team - Experience architecting, migrating, transforming or modernizing customer requirements to the cloud - Experience with presentations and speaking with executives, IT, management, and developers - BS degree in computer science or equivalent, or 4+ years of technical work experience - History of successful technical consulting and/or architecture engagements with large-scale customers or enterprises - Track record of thought leadership and innovation around Responsible AI. Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company's reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you're applying in isn't listed, please contact your Recruiting Partner. The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits . USA, CA, East Palo Alto - 183,000.00 - 247,600.00 USD annually USA, NY, New York - 175,100.00 - 236,900.00 USD annually USA, TX, AUSTIN - 159,200.00 - 215,300.00 USD annually USA, VA, Arlington - 159,200.00 - 215,300.00 USD annually USA, WA, Seattle - 159,200.00 - 215,300.00 USD annually

    Numbers & Facts

    LocationSeattle, WA
    IndustryOther/Not Classified
    Company Size10,000 employees or more
    Year Founded1994
    Websitehttp://Amazon.com/militaryroles

    About Company

    At Amazon, we don’t wait for the next big idea to present itself. We envision the shape of impossible things and then we boldly make them reality. So far, this mindset has helped us achieve some incredible things. Let’s build new systems, challenge the status quo, and design the world we want to live in. We believe the work you do here will be the best work of your life.

    Wherever you are in your career exploration, Amazon likely has an opportunity for you. Our research scientists and engineers shape the future of natural language understanding with Alexa. Fulfillment center associates around the globe send customer orders from our warehouses to doorsteps. Product managers set feature requirements, strategy, and marketing messages for brand new customer experiences. And as we grow, we’ll add jobs that haven’t been invented yet.

    It’s Always Day 1
    At Amazon, it’s always “Day 1.” Now, what does this mean and why does it matter? It means that our approach remains the same as it was on Amazon’s very first day – to make smart, fast decisions, stay nimble, invent, and stay focused on delighting our customers. In our 2016 shareholder letter, Amazon CEO Jeff Bezos shared his thoughts on how to keep up a Day 1 company mindset. “Staying in Day 1 requires you to experiment patiently, accept failures, plant seeds, protect saplings, and double down when you see customer delight,” he wrote. “A customer-obsessed culture best creates the conditions where all of that can happen.” You can read the full letter here

    Our Leadership Principles
    Our Leadership Principles help us keep a Day 1 mentality. They aren’t just a pretty inspirational wall hanging. Amazonians use them, every day, whether they’re discussing ideas for new projects, deciding on the best solution for a customer’s problem, or interviewing candidates. To read through our Leadership Principles from Customer Obsession to Bias for Action, visit https://www.amazon.jobs/principles

    Skills

    • Algorithmsunmatched
    • Amazon Web Services (AWS)unmatched
    • Architectural Servicesunmatched
    • Artificial Intelligence (AI)unmatched
    • Best Practicesunmatched
    • Blogunmatched
    • Blueprintsunmatched
    • Business Developmentunmatched
    • Business Operationsunmatched
    • Cloud Computingunmatched
    • Communication Skillsunmatched
    • Computer Scienceunmatched
    • Consultingunmatched
    • Corporate Policiesunmatched
    • Customer Acquisitionunmatched
    • Customer Support/Serviceunmatched
    • Data Managementunmatched
    • Data Scienceunmatched
    • Data Visualizationunmatched
    • Develop Methodologiesunmatched
    • Distributed Applicationsunmatched
    • Federal Laws and Regulationsunmatched
    • Governmentunmatched
    • Identify Issuesunmatched
    • MATLABunmatched
    • Machine Learningunmatched
    • Market Entry Strategyunmatched
    • Marketingunmatched
    • Math Softwareunmatched
    • Mentoringunmatched
    • People Managementunmatched
    • Presentation/Verbal Skillsunmatched
    • Problem Solving Skillsunmatched
    • Prototypingunmatched
    • Python Programming/Scripting Languageunmatched
    • R Programming Languageunmatched
    • Resolve Customer Issuesunmatched
    • SQL (Structured Query Language)unmatched
    • Salesunmatched
    • Sales Pipelineunmatched
    • Scripting (Scripting Languages)unmatched
    • State Laws and Regulationsunmatched
    • Statistical Analysis System (SAS)unmatched
    • Statistical Modelingunmatched
    • Statistics Softwareunmatched
    • Tableauunmatched
    • Technical Consultingunmatched
    • Technical Leadershipunmatched
    • Thought Leadershipunmatched
    • White Papersunmatched

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