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Applied Scientist, AWS Infrastructure Services Science

Amazon Web Services (AWS) · Arlington, VA · 1 mo ago
AnalystFull-time
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. The posting includes description (role), responsibilities (Key job responsibilities), basic qualifications, preferred qualifications, benefits, pay (salary range), schedule? No schedule info. So we include About the role (description), Responsibilities, Requirements (maybe combine basic qualifications?), Qualifications (preferred?), Skills (maybe programming languages?), Benefits, Pay. Must not repeat job title. Must not include Job ID. Must not include boilerplate like EEO, accommodation, etc. Must preserve all substantive info. Must not invent or summarize away detail. Must not include placeholder text. Must not include sections with filler. We need to parse content: Description: first paragraph about AISS, applied scientist role, etc. That's the role description. Key job responsibilities: bullet list (actually sentences). We'll put as
  • . Basic Qualifications: list of items. Preferred Qualifications: list. Benefits: described: comprehensive benefits including health insurance..., 401(k) matching, paid time off, parental leave. Also mention sign-on payments and RSUs? That's compensation but not benefits? It says "Your Amazon package will include sign-on payments and restricted stock units (RSUs)." That's part of compensation. Could be under Pay? But we have Pay section for salary range. Benefits section can include health insurance, 401(k), PTO, parental leave. Also mention sign-on payments and RSUs maybe under Pay? But they said "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." So we could include that in Pay section? But Pay section is for salary range. Might be okay to include sign-on and RSUs under Pay as additional compensation. However instructions: only create Pay section if posting actually states them. It does state base salary range and mentions sign-on payments and RSUs. So we can include Pay section with that info. Schedule: none, so omit. Skills: maybe we can extract programming languages etc from qualifications. But we already have qualifications sections. Could create Skills section for programming languages, SQL, ML, etc. But we risk duplication. Better to keep qualifications separate. The instruction: Use sections only when posting has real specific content. We have Basic Qualifications and Preferred Qualifications. Could combine into Requirements and Qualifications? They said use headings like About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. So we need to map content to those headings. Likely: - About the role: description paragraph. - Responsibilities: Key job responsibilities. - Requirements: Basic Qualifications. - Qualifications: Preferred Qualifications. - Skills: maybe programming languages etc? But those are already in Requirements. Could still create Skills with programming languages, SQL, ML, etc. But that would duplicate content from Requirements. However we must preserve ALL substantive information; we can include it in both places? Might be redundant but not prohibited. However better to avoid duplication? Not explicitly forbidden, but we should not invent or summarize away detail. Duplication is okay as long as we preserve info. But we could also omit Skills if we think it's covered. The instruction: "Prefer a few substantive sections over many thin ones." So maybe we skip Skills and keep Requirements and Qualifications. Thus sections: About the role, Responsibilities, Requirements, Qualifications, Benefits, Pay. Check if Benefits section has real specific content: yes, they list health insurance, 401(k), PTO, parental leave, etc. Also mention sign-on payments and RSUs? That's compensation but could be under Pay. We'll include Benefits as described. Pay: base salary range and mention sign-on payments and RSUs. Now produce HTML. We must not include /. Just fragment. We'll wrap each section in appropriate tags:

    About the role

    then

    ...

    . For lists:
    • ...
    . Need to preserve all substantive info: ensure we don't lose any details. Let's extract description text: "AWS Infrastructure Services Science (AISS) researches and builds machine learning models that influence the power utilization at our data centers to ensure the health of our thermal and electrical infrastructure at high infrastructure utilization. As an Applied Scientist, you will work on our Science team and partner closely with other scientists, data engineers and Software teams to accurately model and optimize our power infrastructure. Outputs from your models will directly influence our data center topology and will drive exceptional cost savings. You will be responsible for researching and deploying machine learning models that optimize our power and thermal infrastructure, working across AWS to solve data mapping and quality issues and contribute to our Science team vision. You are skeptical. When someone gives you a data source, you pepper them with questions about sampling biases, accuracy, and coverage. When you’re told a model can make assumptions, you proactively try to break those assumptions. You have passion for excellence. The wrong choice of data could cost the business dearly. You maintain rigorous standards and take ownership of the outcome of your data pipelines and code. You raise the bar on the software code standards to delivery faster and efficient solutions. You do whatever it takes to add value. You don’t care whether you’re building complex ML models, writing blazing fast code, integrating multiple disparate data-sets, or creating baseline models - you care passionately about stakeholders and know that as a curator of data insight you can unlock massive cost savings and preserve customer availability. You have a limitless curiosity. You constantly ask questions about the technologies and approaches we are taking and are constantly learning about industry best practices you can bring to our team. You have excellent business and communication skills to be able to work with product owners to understand key business questions and earn the trust of senior leaders. You will need to learn Data Center architecture and components of electrical engineering to build your models. You are comfortable juggling competing priorities and handling ambiguity. You thrive in an agile and fast-paced environment on highly visible projects and initiatives. The tradeoffs of cost savings and customer availability are constantly up for debate among senior leadership - you will help drive this conversation. This position requires superior analytical thinkers, able to quickly approach large ambiguous problems and apply their technical and statistical knowledge to identify opportunities for further research. You should be able to independently mine and analyze data, and be able to use any necessary programming and statistical analysis software to do so. Successful candidates must thrive in fast-paced environments which encourage collaborative and creative problem solving, be able to measure and estimate risks, constructively critique peer research, and align research focuses with the Amazon’s strategic needs." That's the description. Now responsibilities: "Key job responsibilities Leverage deep expertise in one or more scientific disciplines to invent solutions to ambiguous ads measurement problems Disambiguate problems to propose clear evaluation frameworks and success criteria Work autonomously and write high quality technical documents Implement a significant portion of critical-path code, and partner with engineers to directly carry solutions into production Work closely with other scientists to deliver impactful customer solutions Share and publish works with the broader scientific community through meetings and conferences Communicate clearly to scientific audiences" We need to split into bullet points. Each sentence separated by space? We'll make each as
  • . Now basic qualifications: list: - Master's degree - Experience programming in Java, C++, Python or related language - Experience with SQL and an RDBMS (e.g., Oracle) or Data Warehouse - Experience building machine learning models or developing algorithms for business application - Experience implementing algorithms using toolkits and self-developed code - Have publications on top-tier conferences, such as CVPR, ICCV, ECCV or NeurIPS Now preferred qualifications: - Experience researching about machine learning, deep learning, NLP, computer vision, data science - PhD in computer science, mathematics, statistics, machine learning or equivalent quantitative field Now benefits: "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." Also earlier: "Your Amazon package will include sign-on payments and restricted stock units (RSUs)." That's compensation but we can include in Pay. 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. USA, VA, Arlington - 136,000.00 - 184,000.00 USD annually USA, VA, Herndon - 136,000.00 - 184,000.00 USD annually USA, WA, Seattle - 136,000.00 - 184,000.00 USD annually" We need to preserve all substantive info: include salary ranges for three locations. We should not include location headings? It's just info. We'll include as

    with the ranges. Now ensure we don't include boilerplate: remove EEO, accommodation, etc. Also remove "Company - Amazon Web Services, Inc." and "Job ID: A10554058". Also remove "Learn more about our benefits at https://amazon.jobs/en/benefits." That's a link; we should drop as it's navigation/instruction. Also remove "If you have a disability..." etc. Now produce HTML. Structure:

    About the role

    ...

    Responsibilities

    • Leverage deep expertise in one or more scientific disciplines to invent solutions to ambiguous ads measurement problems
    • Disambiguate problems to propose clear evaluation frameworks and success criteria
    • Work autonomously and write high quality technical documents
    • Implement a significant portion of critical-path code, and partner with engineers to directly carry solutions into production
    • Work closely with other scientists to deliver impactful customer solutions
    • Share and publish works with the broader scientific community through meetings and conferences
    • Communicate clearly to scientific audiences

    Requirements

    • Master's degree
    • Experience programming in Java, C++, Python or related language
    • Experience with SQL and an RDBMS (e.g., Oracle) or Data Warehouse
    • Experience building machine learning models or developing algorithms for business application
    • Experience implementing algorithms using toolkits and self-developed code
    • Have publications on top-tier conferences, such as CVPR, ICCV, ECCV or NeurIPS

    Qualifications

    • Experience researching about machine learning, deep learning, NLP, computer vision, data science
    • PhD in computer science, mathematics, statistics, machine learning or equivalent quantitative field

    Benefits

    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.

    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. USA, VA, Arlington - 136,000.00 - 184,000.00 USD annually; USA, VA, Herndon - 136,000.00 - 184,000.00 USD annually;

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