Applied Scientist, Agentic WorkSpaces (AAWS)

We need to output HTML fragment with sections: About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. Only include sections that have real specific content. We must not repeat job title. Must not include Job ID etc. Must preserve all substantive info, no invention. Remove boilerplate like EEO, legal, etc. Also remove duplicated lines, navigation, cookie, etc. We need to parse the description. Key parts: - Description paragraph about AWS Applied AI Solutions etc. - "Key job responsibilities" list (multiple bullet-like sentences). We need to put under Responsibilities section as

• . - "About The Team" paragraph. - "Diverse Experiences" paragraph (maybe part of About the team? but it's a separate statement encouraging candidates). Could be part of About the role? Might be considered generic but it's substantive. However we need to decide sections. - "Why AWS?" paragraph. - "Inclusive Team Culture" paragraph. - "Mentorship & Career Growth" paragraph. - "Work/Life Balance" paragraph. - "Basic Qualifications" list. - "Preferred Qualifications" list. - "Benefits" paragraph (mentions comprehensive benefits including health insurance etc). Also mention sign-on payments and RSUs. - Pay: "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." Then later: "USA, WA, Seattle - 142,800.00 - 193,200.00 USD annually". So we have pay info. - Schedule: Not mentioned explicitly. No schedule info. So we should not create Schedule section. - Skills: Not explicitly listed as a separate section; but we have programming languages etc under qualifications. Could treat as Skills section? The instruction says use sections only when posting has real specific content for it. There's no explicit "Skills" heading, but we could infer skills from qualifications. However better to follow the headings: About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. We have content for About the role (maybe combine description and team etc). Responsibilities we have. Requirements maybe Basic Qualifications? Qualifications maybe Preferred Qualifications? Skills maybe we could extract from qualifications (programming languages, algorithms etc). But we already have those under qualifications. Might be redundant. Better to map: Basic Qualifications -> Requirements. Preferred Qualifications -> Qualifications. Skills maybe not needed; we could omit Skills section if no explicit skills list beyond qualifications. But we have programming languages etc; could be considered skills. However to avoid thin sections, maybe combine them into Qualifications. The instruction: "Prefer a few substantive sections over many thin ones." So we could have About the role, Responsibilities, Requirements (Basic Qualifications), Qualifications (Preferred Qualifications), Benefits, Pay. That's six sections. Omit Skills and Schedule. We must not include headings with filler text. Ensure each section has substantive content. Now we need to preserve all substantive information; do not invent or summarize away detail. So we need to keep all details from the description, but we can reformat into HTML. We must remove boilerplate: EEO, equal-opportunity, scam-warning, cookie/navigation/legal, duplicated lines, application instructions. Also remove "Amazon is an equal opportunity employer..." etc. Also remove "If you have a disability..." etc. Also remove "Learn more about our benefits at https://..." maybe keep benefits description but not the link? The instruction: remove cookie/navigation/legal/EEO/equal-opportunity/scam-warning boilerplate, duplicated lines, and application instructions. The link to benefits might be considered navigation? It's a link; but it's part of benefits description. Might be okay to keep but it's a link; maybe we should remove the link as it's navigation. Safer to remove the URL. Keep the description of benefits. Also remove "If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner." That's application instruction; remove. Also remove "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." That's part of pay; we keep but maybe rephrase? We must preserve all substantive information; we can keep that sentence. Also remove "USA, WA, Seattle - 142,800.00 - 193,200.00 USD annually" keep as pay. Now we need to structure. Let's extract sections: About the role: Could combine the initial description paragraphs: "AWS Applied AI Solutions (AAIS) is where science meets customer obsession at scale..." plus "About The Team" maybe? But About The Team is separate heading. Could treat About the role as the first paragraph(s) before responsibilities. About The Team could be part of About the role or separate? The instruction says use headings for section headings like About the role, Responsibilities, etc. So we should have About the role section containing the description of the role and team? The "About The Team" paragraph is about the team; could be part of About the role. We'll include it there. Thus About the role content: first paragraph about AAIS and WorkSpaces, then "About The Team" paragraph, plus maybe "Diverse Experiences", "Why AWS?", "Inclusive Team Culture", "Mentorship & Career Growth", "Work/Life Balance". Those are more about AWS culture; could be part of About the role as well. But to avoid too thin sections, we can put them all under About the role. But we must preserve all substantive information; we can include them as paragraphs. Responsibilities: list of responsibilities from "Key job responsibilities". We'll bullet each sentence. Requirements: Basic Qualifications list. Qualifications: Preferred Qualifications list. Benefits: paragraph about benefits (including health insurance etc) plus mention of sign-on payments and RSUs? Actually sign-on payments and RSUs mentioned under pay; but we can keep them in Pay section. Benefits: health insurance, 401(k) matching, paid time off, parental leave. Also mention "Learn more about our benefits at ..." we will drop the link. Pay: base salary range, sign-on payments, RSUs, final compensation determination. Schedule: none -> omit. Now we need to output HTML fragment only. We'll wrap each section in appropriate tags:

  About the role

  then

  ... maybe multiple paragraphs. For lists,

  • ...
  . We must not include or . Let's craft. First, About the role: Paragraph 1: "AWS Applied AI Solutions (AAIS) is where science meets customer obsession at scale. We build the intelligent systems that power AWS services used by millions, combining research in machine learning, agentic AI, and applied science with the operational rigor required to deliver enterprise grade experiences. Within AAIS, Amazon WorkSpaces is our cloud based virtual desktop service that delivers secure, managed computing to over one million daily users across the globe, enabling organizations to provision, manage, and scale desktops with the reliability and performance their workforce depends on. We are looking for an Applied Scientist to be part of the tiger team building the capacity modelling for Amazon WorkSpaces, owning and advancing the science behind it. You will design, build, and continuously improve the forecasting and optimization models that ensure the right compute, storage, and networking resources are available at the right time, in the right regions, at the lowest possible cost, without ever compromising the end user experience. This is a high impact individual contributor role for someone who thrives at the intersection of applied research and production systems. You will define the scientific roadmap for capacity intelligence, turning reactive provisioning into a predictive, self optimizing engine that anticipates demand before customers feel any constraint." Paragraph 2: About The Team: "As part of the AWS solutions organization, we have a vision to provide business applications, leveraging Amazon's unique experience and expertise, that are used by millions of companies worldwide to manage day-to-day operations. We will accomplish this by accelerating our customers' businesses through delivery of intuitive and differentiated technology solutions that solve enduring business challenges. we blend vision with curiosity and Amazon's real-world experience to build opinionated, turnkey solutions. Where customers prefer to buy over build, we become their trusted partner with solutions that are no-brainers to buy and easy to use." Paragraph 3: Diverse Experiences: "AWS values diverse experiences. Even if you do not meet all of the preferred 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." Paragraph 4: Why AWS?: "Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses." Paragraph 5: Inclusive Team Culture: "AWS values curiosity and connection. Our employee-led and company-sponsored affinity groups promote inclusion and empower our people to take pride in what makes us unique. Our inclusion events foster stronger, more collaborative teams. Our continual innovation is fueled by the bold ideas, fresh perspectives, and passionate voices our teams bring to everything we do." Paragraph 6: Mentorship & Career Growth: "We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional." Paragraph 7: Work/Life Balance: "We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve." Now Responsibilities: list each bullet from "Key job responsibilities". Let's extract each sentence: - Define and drive the scientific strategy for capacity modelling, establishing the research agenda that transforms how WorkSpaces forecasts demand, plans supply, and allocates resources across a globally distributed infrastructure. - Build advanced demand forecasting models that predict workspace usage across multiple time horizons, from intraday spikes to long range growth trajectories, incorporating signals such as customer onboarding patterns, seasonal trends, regional expansion, and macroeconomic indicators. - Design supply optimization frameworks that determine optimal resource placement, instance mix, and pre warming strategies, balancing availability, performance, and cost by reasoning over hardware constraints, pricing dynamics, and service level objectives. - Develop causal and probabilistic models that move beyond trend extrapolation to true understanding of demand drivers, enabling the organization to distinguish organic growth from one time events, anticipate shifts in usage patterns, and quantify uncertainty in planning decisions. - Architect simulation and scenario planning systems that allow business and engineering leaders to run what if analyses, stress test capacity plans against disruption scenarios, and evaluate trade offs between investment timing, risk tolerance, and customer experience. - Pioneer the integration of machine learning with operations research, combining deep learning based forecasting with mathematical optimization to jointly solve the demand prediction and resource allocation problem in a way that neither discipline can achieve alone. - Establish evaluation frameworks and monitoring systems that measure forecast accuracy, capacity utilization, and cost efficiency in production, creating tight feedback loops that drive continuous model improvement and build organizational trust in science driven planning. - Influence the broader organization's capacity strategy by translating model outputs into actionable recommendations for leadership, identifying opportunities to extend capacity intelligence patterns to adjacent services, and mentoring scientists and engineers across the team. We'll put each as
• . Now Requirements (Basic Qualifications): List: - 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 in patents or publications at top-tier peer-reviewed conferences or journals - Experience programming in Java, C++, Python or related language - Experience in any of the following areas: algorithms and data structures