Senior Applied Scientist, Advertising

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. No metadata like Job ID. Remove boilerplate like EEO, accommodation links, etc. Keep substantive info. We need to parse description. Sections: - About the role: description paragraph about orchestrating selection, demand retrieval team, looking for Applied Scientist, etc. Could be a paragraph. - Responsibilities: bullet list of key job responsibilities (Design and implement deep learning models..., Investigate new ML techniques..., Improve performance..., Work side by side..., Rapidly prototype..., Be immersed..., Understand latest literature...). Also maybe "A day in the life" could be part of responsibilities or separate? But we can include as responsibilities. - Requirements: Basic Qualifications: 3+ years building ML models for business application experience; PhD, or Master's degree and 6+ years of applied research experience; Experience programming in Java, C++, Python or related language; Experience with neural deep learning methods and machine learning. - Qualifications: Preferred Qualifications: Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.; Experience with large scale distributed systems such as Hadoop, Spark etc. - Skills: maybe combine technical skills? Could include programming languages, ML methods, etc. But we already have those in qualifications. Could create Skills section for things like strong technical ability, teamwork, communication, motivation, etc. The description mentions: Successful candidates will have strong technical ability, excellent teamwork, communication skills, and a motivation to achieve business results in a fast-paced environment. That's more like skills/attributes. - Benefits: The posting mentions: "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." Also link to benefits. So we can include Benefits section with that list. - Pay: The posting includes: "The base salary range for this position is listed below. USA, NY, New York - 183,800.00 - 248,700.00 USD annually". So we have Pay section with that range. - Schedule: Not mentioned. No schedule info. So we should not include Schedule section. We must not include boilerplate like EEO, accommodation, etc. Also remove duplicated lines. We need to use

for section headings. Use

• for any list of duties/requirements/benefits. Use

  for prose. We need to preserve all substantive information; do not invent or summarize away detail. So we need to keep the specifics: e.g., "Design and implement deep learning models to match the right customers with the right ads across different verticals, geographies, and ads formats." etc. We need to ensure we don't create sections with filler like "commensurate with experience". Not present. We need to output only HTML fragment, no /, no markdown fences. Let's craft. Structure:

  About the role

  Orchestrating the selection of one out of tens of millions of ads, honoring advertiser targeting intent for hundreds of thousands of advertisers while ensuring great shopper experience for billions of shoppers millions of times per second on a latency of tens of milliseconds is not a trivial task. The demand retrieval team within the Amazon DSP organisation deals with this challenge, developing and operating machine learning models that match ads opportunities with the most relevant ads to deliver the right messages to the right customers at the right time. We are looking for an Applied Scientist to optimize ad matching for Amazon’s programmatic advertisement products. In this role you will lead the design and implementation of solutions for performance sourcing, using behavioural information on customers’ interactions with Amazon and other owned and operated businesses as well as contextual information about the bid request to predict their propensity to convert, in turn driving better advertising campaign outcomes. Your work will affect multi-billion dollar businesses, and you will be responsible for designing, testing and delivering significant breakthrough's for Amazon's business. Successful candidates will have strong technical ability, excellent teamwork, communication skills, and a motivation to achieve business results in a fast-paced environment.

  Responsibilities

  • Design and implement deep learning models to match the right customers with the right ads across different verticals, geographies, and ads formats.
  • Investigate new ML techniques such as multi-task learning to ensure that models can operate for a variety of advertisers in multiple industries and with different volumes of conversion events.
  • Improve the performance, generalisation and scalability of models by introducing new features and enhancing models’ architecture.
  • Work side by side with our engineers to deliver code changes impacting our ads stack, working with very large datasets and high throughput production systems.
  • Rapidly prototype and test many possible hypotheses/implementation alternatives in a high-ambiguity environment, making use of both quantitative analysis and business judgement.
  • Be immersed in Amazon's advertisers and their objectives, and think long-term about how to turn those objectives into products and technical capabilities.
  • Understand the latest literature on machine learning for recommender and advertising systems, contributing to guiding strategic investment for the organization.
  Optionally include "A day in the life" as part of responsibilities? Could add a paragraph after list? But we already captured responsibilities. The "A day in the life" paragraph: "You will partner with our product and engineering teams, bringing your own ideas to the conversation and aligning on work, adjusting priorities based on business requirements and fast iteration on experiments. You will have a strong theoretical understanding of modern ML techniques and methodologies, and the software engineering and data processing skills to deploy these using the large-scale datasets we deal with in advertising." This is also substantive; could be added as another
• or as a paragraph under Responsibilities. Since it's about day-to-day, we can add as another
• . Let's add.

  Requirements

  • 3+ years of building machine learning models for business application experience
  • PhD, or Master's degree and 6+ years of applied research experience
  • Experience programming in Java, C++, Python or related language
  • Experience with neural deep learning methods and machine learning

  Qualifications

  • Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.
  • Experience with large scale distributed systems such as Hadoop, Spark etc.

  Skills

  Strong technical ability, excellent teamwork, communication skills, and motivation to achieve business results in a fast-paced environment.

  Benefits

  • Sign-on payments and restricted stock units (RSUs)
  • Comprehensive health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance, 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
  • Parental leave

  Pay

  Base salary range: $183,800.00 – $248,700.00 USD annually (USA, NY, New York)

  We should not include Schedule. Check for any duplicated lines: we removed EEO, accommodation, etc. Make sure we didn't include any boilerplate like "Amazon is an equal opportunity employer". Removed. Check that we preserved all substantive info: The description about orchestrating selection, demand retrieval team, etc. Included. The "A day in the life" content added as li. The "About The Team" paragraph: we didn't include that explicitly. The "About The Team" section: "The Demand Retrieval team is responsible for designing, implementing, deploying and operating machine learning models that match bid opportunities to ads demand based on performance, campaign delivery, and targeting objectives specified by advertisers. We measure the success of our approaches based on offline experimentation and and online metrics that measure the impact of our matching models on campaign KPIs (e.g.: cost per action, return on ads investment, budgets delivered, and targeting precision)." This is substantive; we missed it. Should we include it? It could be part of About the role or a separate section like "About the team". Since we have only predefined headings, we could add it under About the role as additional paragraph. Or we could create a new section but only allowed headings list; we could add it under About the role. Let's incorporate that into About the role paragraph after the initial description. Thus About the role paragraph will be longer, containing both the initial description and the About The Team content. Let's rewrite About the role:

  Orchestrating the selection of one out of tens of millions of ads, honoring advertiser targeting intent for hundreds of thousands of advertisers while ensuring great shopper experience for billions of shoppers millions of times per second on a latency of tens of milliseconds is not a trivial task. The demand retrieval team within the Amazon DSP organisation deals with this challenge, developing and operating machine learning models that match ads opportunities with the most relevant ads to deliver the right messages to the right customers at the right time. We are looking for an Applied Scientist to optimize ad matching for Amazon’s programmatic advertisement products. In this role you will lead the design and implementation of solutions for performance sourcing, using behavioural information on customers’ interactions with Amazon and other owned and operated businesses as well as contextual information about the bid request to predict their propensity to convert, in turn driving better advertising campaign outcomes. Your work will affect multi-billion dollar businesses, and you will be responsible for designing, testing and delivering significant breakthrough's for Amazon's business. Successful candidates will have strong technical ability, excellent teamwork, communication skills, and a motivation to achieve business results in a fast-paced environment. The Demand Retrieval team is responsible for designing, implementing, deploying and operating machine learning models that match bid opportunities to ads demand based on performance, campaign delivery, and targeting objectives specified by advertisers. We measure the success of our approaches based on offline experimentation and online metrics that measure the impact of our matching models on campaign KPIs (e.g.: cost per action, return on ads investment, budgets delivered, and targeting precision).

  Now we have covered. Check for any other substantive: "A day in the life" we added as li under Responsibilities. Good. Check for any mention of "sign-on payments and restricted stock units (RSUs)" we added under Benefits. Check for "Learn more about our benefits at https://amazon.jobs/en/benefits." That's a link; we could include as part of Benefits but it's a reference; we could keep as a sentence but it's not essential; but we can include as a

  maybe. However it's a link; we could include as part of Benefits

  Learn more about our benefits at https://amazon.jobs/en/benefits.

  But the instruction says preserve ALL substantive information; do not invent or summarize away detail. So we should keep that link. However it's a URL; we can include as a

  under Benefits. Similarly there is a link for accommodations but we removed as boilerplate. The benefits link is not boilerplate; it's substantive. So we should keep. Thus Benefits section:

  list plus maybe a

  with the link. Let's