Kevin Small
Kevin Small is a senior applied scientist within the Alexa organization, and has been involved in organizing many of Amazon’s internal conferences in his more than five years at Amazon.
Credit: Arun Krishnan

Amazon’s internal conferences build a sense of community: Kevin Small

Kevin Small has been involved in organizing many of Amazon’s internal conferences in his more than five years at Amazon. In this conversation, Kevin explains how Amazon’s internal conferences facilitate important breakthroughs, forge collaborations between groups, and help advance one’s career.

Amazon hosts internal conferences throughout the year to connect the company’s scientists to each other, and to the academic community at large. For example, the Amazon Machine Learning Conference brings together thousands of scientists and engineers to share research results and raise the scientific bar within the company.

Kevin Small is a senior applied scientist within the Alexa organization, and has been involved in organizing many of Amazon’s internal conferences in his more than five years at Amazon. In this conversation, Small explains how Amazon’s internal conferences facilitate important breakthroughs, forge collaborations between groups, and help advance one’s career.

Q. You were an academic prior to working at Amazon. What attracted you to Amazon?

A. I held a research faculty appointment at Tufts Medical Center. We were developing machine learning methods for reducing the manual effort required by doctors when generating systematic reviews. Our work has been used by several Evidence-based Practice centers, with the resulting reports included in the Cochrane Database of Systematic Reviews.

When I joined Amazon, I had planned on it being a one-year intermission between academic positions to get first-hand insight regarding conducting science in a business setting. At the time, machine learning was having an increasingly greater impact on our industry, and I was curious where the field was headed. Amazon offered an incredible opportunity to leverage the company’s computational resources and collaborate with peers to solve problems that make an impact on the lives of our customers.

One thing I find exciting about Amazon is that even my more incremental work has an opportunity to have an impact at scale, which in turn helps point me toward more important problems. For example, one of my first projects was to automate the understanding of customer reviews on amazon.com, a project that helped millions of customers make better purchasing decisions.

I also liked how people worked as peers at Amazon, which was in contrast to the more hierarchical structure of academia. At Amazon, for everything I have worked on, I have always felt part of a larger team and appreciate that even the most junior team members have ownership and agency, and function as a part of a larger community.

Q. It’s interesting you bring up being drawn to a sense of community. Is this why you’ve been involved in organizing internal conferences?

I’ve always enjoyed being a part of the larger academic community. I review papers for conferences like NeurIPS, ICML, AAAI, and ACL, amongst others throughout the year. I wanted to extend my involvement and grow the sense of community within Amazon as well. This feeling of being part of something larger, along with peer feedback, is absolutely vital to researchers and scientists.

Organizing internal conferences is especially important at a company like ours. As you know, Amazon is different from many other companies when it comes to the way our science and research teams are organized. In general, we are spread across business units, as opposed to being part of a central organization. When I joined Amazon, there were fewer formal mechanisms to connect scientists across the company in an intentional way. Thus, we began to work on conferences like AMLC to address this gap.

Q. When we solve customer problems, there's a need for an interdisciplinary kind of approach. Do you feel these conferences help in fostering interdisciplinary thinking?

Definitely. Customer problems are rarely solved within a single scientific discipline. For example, within the Alexa organization, scientists might be interested in developing the best speech recognition or question answering systems. But they are working on this for customers who are looking to find music, to open their garage doors or turn on the lights in their house. This requires experts in multi-modal UX design, systems engineering, computational considerations, operational excellence, and a number of fields working together. We structure our internal conferences in way that scientists almost have no choice but to think about how their work fits in this ecosystem.

As a specific example, there was a paper presented this year at AMLC on the Amazon Photos face clustering problem -- the task of grouping all the photos of a distinct individual with little to preferably no supervision from the customer. The paper described the end-to-end process, from collecting evaluation data to training of embedding models and associated context modeling techniques. This paper brought together scientists from various business units within Amazon, and highlighted that solving customer problems requires collaboration across multiple business units.

Q. How do you determine the kind of content you want to feature at a conference?

For conferences like AMLC where we bring in researchers from across the company, we first look for papers that feature breakthrough work. These are papers with implications for a broader segment of the scientific community.

Of course, true breakthroughs are rare. Thus, we also feature papers from at least two other families of contributions. First, we showcase work demonstrating notable progress on really important customer problems – for example, improving the engagement with product recommendations served on the site or reducing delivery times to customers. Secondly, we like to highlight exemplary work regarding ML pipelines that might serve as templates for work throughout the company.

Conferences can also help scientists prioritize what they should be working on. At Amazon, scientists frequently measure their contributions by the impact that their innovations have had on the business at large and scientific priorities are often correlated with business needs. However, sometimes, they are not perfectly aligned for more disruptive research directions. These conferences provide an opportunity to set an agenda for our scientists, where we identify areas where they can discuss how to deliver longer-term meaningful innovation to customers.

Q. How do you see conferences at Amazon evolving?

Over the last five years, our internal data suggests that the number of accepted publications from our scientists at external conferences has gone up by an estimated 500%. You’ll continue to see increased participation from Amazon at external conferences as we encourage our interns and employees to publish externally even more.

I also expect the kind of papers we present at internal conferences to evolve and reflect more real-world scenarios. For example, when you talk about areas like personalization or advertising, you find that real-world data behaves very differently from offline data sets. The distribution of real-world data is often non-stationary or even adversarial. In addition, the fact that people begin to use a system changes related feedback loops, which in turn impacts their behavior. For internal conferences, I expect we’ll see papers that focus on these kinds of research problems that might not be as relevant in an academic setting, but which can have a positive impact on the lives of millions of customers.

I also see our conferences evolving in terms of even more mechanisms for scientists to network with each other. The community of scientists and researchers is smaller than you would expect -- getting noticed at an internal conference can do wonders for a scientist’s career in terms of visibility.

Finally, I expect we’ll continue to organize conference like Amazon Research Days, where we focus on networking and building ties with the academic community. This is important because we can’t operate in a vacuum. We benefit from the academic community, and they benefit from our work and resources as well.

Research areas

Related content

US, CA, Santa Clara
Job summaryAmazon is looking for a passionate, talented, and inventive Applied Scientist with a strong machine learning background to help build industry-leading language technology.Our mission is to provide a delightful experience to Amazon’s customers by pushing the envelope in Natural Language Processing (NLP), Natural Language Understanding (NLU), Dialog management, conversational AI and Machine Learning (ML).As part of our AI team in Amazon AWS, you will work alongside internationally recognized experts to develop novel algorithms and modeling techniques to advance the state-of-the-art in human language technology. Your work will directly impact millions of our customers in the form of products and services, as well as contributing to the wider research community. You will gain hands on experience with Amazon’s heterogeneous text and structured data sources, and large-scale computing resources to accelerate advances in language understanding.We are hiring primarily in Conversational AI / Dialog System Development areas: NLP, NLU, Dialog Management, NLG.This role can be based in NYC, Seattle or Palo Alto.Inclusive Team CultureHere at AWS, we embrace our differences. We are committed to furthering our culture of inclusion. We have ten employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. We have innovative benefit offerings, and host annual and ongoing learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences.Work/Life BalanceOur team puts a high value on work-life balance. It isn’t about how many hours you spend at home or at work; it’s about the flow you establish that brings energy to both parts of your life. We believe striking the right balance between your personal and professional life is critical to life-long happiness and fulfillment. We offer flexibility in working hours and encourage you to find your own balance between your work and personal lives.Mentorship & Career GrowthOur team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and we’re building an environment that celebrates knowledge sharing and mentorship. Our senior members enjoy one-on-one mentoring and thorough, but kind, code reviews. We care about your career growth and strive to assign projects based on what will help each team member develop into a better-rounded engineer and enable them to take on more complex tasks in the future.
US, NY, New York
Job summaryAmazon is looking for a passionate, talented, and inventive Applied Scientist with a strong machine learning background to help build industry-leading language technology.Our mission is to provide a delightful experience to Amazon’s customers by pushing the envelope in Natural Language Processing (NLP), Natural Language Understanding (NLU), Dialog management, conversational AI and Machine Learning (ML).As part of our AI team in Amazon AWS, you will work alongside internationally recognized experts to develop novel algorithms and modeling techniques to advance the state-of-the-art in human language technology. Your work will directly impact millions of our customers in the form of products and services, as well as contributing to the wider research community. You will gain hands on experience with Amazon’s heterogeneous text and structured data sources, and large-scale computing resources to accelerate advances in language understanding.We are hiring primarily in Conversational AI / Dialog System Development areas: NLP, NLU, Dialog Management, NLG.This role can be based in NYC, Seattle or Palo Alto.Inclusive Team CultureHere at AWS, we embrace our differences. We are committed to furthering our culture of inclusion. We have ten employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. We have innovative benefit offerings, and host annual and ongoing learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences.Work/Life BalanceOur team puts a high value on work-life balance. It isn’t about how many hours you spend at home or at work; it’s about the flow you establish that brings energy to both parts of your life. We believe striking the right balance between your personal and professional life is critical to life-long happiness and fulfillment. We offer flexibility in working hours and encourage you to find your own balance between your work and personal lives.Mentorship & Career GrowthOur team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and we’re building an environment that celebrates knowledge sharing and mentorship. Our senior members enjoy one-on-one mentoring and thorough, but kind, code reviews. We care about your career growth and strive to assign projects based on what will help each team member develop into a better-rounded engineer and enable them to take on more complex tasks in the future.
US, CA, Santa Clara
Job summaryAWS AI/ML is looking for world class scientists and engineers to join its AI Research and Education group working on building automated ML solutions for planetary-scale sustainability and geospatial applications. Our team's mission is to develop ready-to-use and automated solutions that solve important sustainability and geospatial problems. We live in a time wherein geospatial data, such as climate, agricultural crop yield, weather, landcover, etc., has become ubiquitous. Cloud computing has made it easy to gather and process the data that describes the earth system and are generated by satellites, mobile devices, and IoT devices. Our vision is to bring the best ML/AI algorithms to solve practical environmental and sustainability-related R&D problems at scale. Building these solutions require a solid foundation in machine learning infrastructure and deep learning technologies. The team specializes in developing popular open source software libraries like AutoGluon, GluonCV, GluonNLP, DGL, Apache/MXNet (incubating). Our strategy is to bring the best of ML based automation to the geospatial and sustainability area.We are seeking an experienced Applied Scientist for the team. This is a role that combines science knowledge (around machine learning, computer vision, earth science), technical strength, and product focus. It will be your job to develop ML system and solutions and work closely with the engineering team to ship them to our customers. You will interact closely with our customers and with the academic and research communities. You will be at the heart of a growing and exciting focus area for AWS and work with other acclaimed engineers and world famous scientists. You are also expected to work closely with other applied scientists and demonstrate Amazon Leadership Principles (https://www.amazon.jobs/en/principles). Strong technical skills and experience with machine learning and computer vision are required. Experience working with earth science, mapping, and geospatial data is a plus. Our customers are extremely technical and the solutions we build for them are strongly coupled to technical feasibility.About the teamInclusive Team CultureAt AWS, we embrace our differences. We are committed to furthering our culture of inclusion. We have ten employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. We have innovative benefit offerings, and host annual and ongoing learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences. Amazon’s culture of inclusion is reinforced within our 14 Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and earn trust. Work/Life BalanceOur team puts a high value on work-life balance. It isn’t about how many hours you spend at home or at work; it’s about the flow you establish that brings energy to both parts of your life. We believe striking the right balance between your personal and professional life is critical to life-long happiness and fulfillment. We offer flexibility in working hours and encourage you to find your own balance between your work and personal lives.Mentorship & Career GrowthOur team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and we’re building an environment that celebrates knowledge sharing and mentorship. Our senior members enjoy one-on-one mentoring. We care about your career growth and strive to assign projects based on what will help each team member develop into a better-rounded scientist and enable them to take on more complex tasks in the future.Interested in this role? Reach out to the recruiting team with questions or apply directly via amazon.jobs.
US, CA, Santa Clara
Job summaryAWS AI/ML is looking for world class scientists and engineers to join its AI Research and Education group working on building automated ML solutions for planetary-scale sustainability and geospatial applications. Our team's mission is to develop ready-to-use and automated solutions that solve important sustainability and geospatial problems. We live in a time wherein geospatial data, such as climate, agricultural crop yield, weather, landcover, etc., has become ubiquitous. Cloud computing has made it easy to gather and process the data that describes the earth system and are generated by satellites, mobile devices, and IoT devices. Our vision is to bring the best ML/AI algorithms to solve practical environmental and sustainability-related R&D problems at scale. Building these solutions require a solid foundation in machine learning infrastructure and deep learning technologies. The team specializes in developing popular open source software libraries like AutoGluon, GluonCV, GluonNLP, DGL, Apache/MXNet (incubating). Our strategy is to bring the best of ML based automation to the geospatial and sustainability area.We are seeking an experienced Applied Scientist for the team. This is a role that combines science knowledge (around machine learning, computer vision, earth science), technical strength, and product focus. It will be your job to develop ML system and solutions and work closely with the engineering team to ship them to our customers. You will interact closely with our customers and with the academic and research communities. You will be at the heart of a growing and exciting focus area for AWS and work with other acclaimed engineers and world famous scientists. You are also expected to work closely with other applied scientists and demonstrate Amazon Leadership Principles (https://www.amazon.jobs/en/principles). Strong technical skills and experience with machine learning and computer vision are required. Experience working with earth science, mapping, and geospatial data is a plus. Our customers are extremely technical and the solutions we build for them are strongly coupled to technical feasibility.About the teamInclusive Team CultureAt AWS, we embrace our differences. We are committed to furthering our culture of inclusion. We have ten employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. We have innovative benefit offerings, and host annual and ongoing learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences. Amazon’s culture of inclusion is reinforced within our 14 Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and earn trust. Work/Life BalanceOur team puts a high value on work-life balance. It isn’t about how many hours you spend at home or at work; it’s about the flow you establish that brings energy to both parts of your life. We believe striking the right balance between your personal and professional life is critical to life-long happiness and fulfillment. We offer flexibility in working hours and encourage you to find your own balance between your work and personal lives.Mentorship & Career GrowthOur team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and we’re building an environment that celebrates knowledge sharing and mentorship. Our senior members enjoy one-on-one mentoring. We care about your career growth and strive to assign projects based on what will help each team member develop into a better-rounded scientist and enable them to take on more complex tasks in the future.Interested in this role? Reach out to the recruiting team with questions or apply directly via amazon.jobs.
US, NY, New York
Job summaryAmazon Web Services is looking for world class scientists to join the Security Analytics and AI Research team within AWS Security Services. This group is entrusted with researching and developing core data mining and machine learning algorithms for various AWS security services like GuardDuty (https://aws.amazon.com/guardduty/) and Macie (https://aws.amazon.com/macie/). In this group, you will invent and implement innovative solutions for never-before-solved problems. If you have passion for security and experience with large scale machine learning problems, this will be an exciting opportunity.The AWS Security Services team builds technologies that help customers strengthen their security posture and better meet security requirements in the AWS Cloud. The team interacts with security researchers to codify our own learnings and best practices and make them available for customers. We are building massively scalable and globally distributed security systems to power next generation services.Inclusive Team Culture Here at AWS, we embrace our differences. We are committed to furthering our culture of inclusion. We have ten employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. We have innovative benefit offerings, and host annual and ongoing learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences. Amazon’s culture of inclusion is reinforced within our 14 Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and earn trust. Work/Life Balance Our team puts a high value on work-life balance. It isn’t about how many hours you spend at home or at work; it’s about the flow you establish that brings energy to both parts of your life. We believe striking the right balance between your personal and professional life is critical to life-long happiness and fulfillment. We offer flexibility in working hours and encourage you to find your own balance between your work and personal lives. Mentorship & Career Growth Our team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and we’re building an environment that celebrates knowledge sharing and mentorship. We care about your career growth and strive to assign projects based on what will help each team member develop and enable them to take on more complex tasks in the future.A day in the lifeAbout the hiring groupJob responsibilities* Rapidly design, prototype and test many possible hypotheses in a high-ambiguity environment, making use of both quantitative and business judgment.* Collaborate with software engineering teams to integrate successful experiments into large scale, highly complex production services.* Report results in a scientifically rigorous way.* Interact with security engineers, product managers and related domain experts to dive deep into the types of challenges that we need innovative solutions for.
US, Virtual
Job summaryDo you have consulting leadership experience deploying digital, data, technology strategy and execution within Fortune 500 enterprise organization? Have you built and led successful consulting practices? Do you have broad technical skills and experience across Machine Learning and Artificial Intelligence? Can you build, lead and influence machine learning engineers and data science consultants in a technical specialty team to deliver these new capabilities on the AWS platform to our enterprise customers? At AWS, we are looking for a Senior Practice Manager with a successful record of leading enterprise customers through a variety of transformative projects involving Machine Learning and Artificial Intelligence; delivering business outcomes that contribute to our customers’ transformation journey. An SPM will focus on a geography and a set of technical specialties, and will manage a team of direct reports. The SPM will develop a long-term plan to develop the right skills across the team, influence the go-to-market strategy within the region and collaborate across the entire AWS organization to bring access to product and service teams, to get the right solution delivered and drive feature innovation based upon customer needs. Key job responsibilities• Engage customers - collaborate with enterprise sales managers to develop strong customer and partner relationships and build a growing business, driving adoption of emerging technologies in key accounts.• Coach and teach - collaborate with field sales, pre-sales, marketing, training and support teams to help partners and customers drive business outcomes through application of AI/ML.• Deliver value - lead high quality delivery of a variety of customized engagements with partners and enterprise customers in the commercial sector.• Lead great people - attract top machine learning engineers and data scientists to build high performing teams of consultants with superior technical depth, and outstanding peer and customer relationship skills• Be a customer advocate - Work with engineering teams to convey partner and enterprise customer feedback as input to technology roadmaps
US, WA, Seattle
Job summaryAWS Insight is looking for a Data Scientist to help develop sophisticated algorithms and models that involve analyzing and learning from over 540 billion customer cost, usage, and utilization events daily. We use this data to generate recommendations and forecasts for customers to help them better understand and optimize their AWS costs and usage and reduce the complexity of managing their cloud costs. Our team's vision is to be the world's authoritative provider of AWS computing insight, where customers can understand, control and optimize usage of AWS products. We sit at the nexus of all AWS services and interact directly with end-customers, and we build relationships with teams across AWS to ensure that we offer a secure and reliable customer experience that builds trust with our customers and provides them with intelligent insights.As a successful data scientist in AWS Insights, you will be responsible for understanding and mining the large amount of data, and developing recommendations that will help improve the accuracy and relevance of our forecasting and recommendations models. You will work closely with talented data scientists, software engineers, and business groups to build enhance existing models and build new models that solve challenging customer problems. You will work with the engineers to drive implementation of the proposed models and establish testing strategies to validate the models before and after they are put into production. On top of that, you are an analytical problem solver who enjoys diving into data, are excited about investigating and developing algorithms, and can influence technical teams and business stakeholders to solve real-world customer problems.Key job responsibilitiesImproving upon existing forecasting statistical or machine learning methodologies by developing new data sources, testing model enhancements, running computational experiments, and fine-tuning model parameters for new forecasting modelsSupporting decision making by providing requirements to develop analytic capabilities, platforms, pipelines and metrics then using them to analyze trends and find root causes of forecast inaccuracyFormalizing assumptions about how demand forecasts are expected to behave, creating definitions of outliers, developing methods to systematically identify these outliers, and explaining why they are reasonable or identifying fixes for themTranslating forecasting business requirements into specific analytical questions that can be answered with available data using statistical and machine learning methods; working with engineers to produce the required data when it is not availableCommunicating verbally and in writing to business customers with various levels of technical knowledge, educating them about our systems, as well as sharing insights and recommendationsUtilizing code (Python, R, Scala, etc.) for analyzing data and building statistical and machine learning models and algorithms
US, Virtual
Job summaryIn the Amazon Selection Monitoring team, we have the goal of establishing the most comprehensive, accurate and fresh universal selection of products. We enrich and increase the quality and coverage of Amazon product selection using cutting edge machine learning and big data technologies. We are looking for highly motivated scientists who can lead the design, development, deployment and maintenance of data-driven models using machine learning (ML) and/or natural language (NL) and computer vision (CV) applications. Your models would be monitoring billions and billions of products. You will build Amazon scale applications running on Amazon Web Service (AWS) that both leverage and create new technologies to process large volumes of data that derive patterns and conclusions from the data. Amazon Science gives you insight into the company’s approach to customer-obsessed scientific innovation. Amazon fundamentally believes that scientific innovation is essential to being the most customer-centric company in the world. It’s the company’s ability to have an impact at scale that allows us to attract some of the brightest minds in artificial intelligence and related fields. Our scientists continue to publish, teach, and engage with the academic community, in addition to utilizing our working backwards method to enrich the way we live and work. Please visit https://www.amazon.science for more information. Responsibilities - Designing and implementing new features and machine learned models, including the application of state-of-art deep learning to solve search matching and ranking problems, including filtering, new content indexing, and apply document understandingConducting and coordinating process development leading to improved and streamlined processes for model development. Strong customer focus is essentialWorking closely with Product Managers to expand depth of our product insights with data, create a variety of experiments, and determine the highest-impact projects to include in planning roadmapsProviding technical and scientific guidance to your team membersCommunicating effectively with senior management as well as with colleagues from science, engineering, and business backgroundsBeing a cultural leader that ensures teams are collecting, understanding, and using data to inform every decision that impacts our customers The successful candidate will have an established background in developing customer-facing experiences, a strong technical ability, a start-up mentality, excellent project management skills, and great communication skills.Key job responsibilitiesDesigning and implementing new features and machine learned models, including the application of state-of-art deep learning to solve search matching and ranking problems, including filtering, new content indexing, and apply document understandingConducting and coordinating process development leading to improved and streamlined processes for model development. Strong customer focus is essentialWorking closely with Product Managers to expand depth of our product insights with data, create a variety of experiments, and determine the highest-impact projects to include in planning roadmapsProviding technical and scientific guidance to your team membersCommunicating effectively with senior management as well as with colleagues from science, engineering, and business backgroundsBeing a cultural leader that ensures teams are collecting, understanding, and using data to inform every decision that impacts our customersA day in the lifeYou will work with Product Managers to translate the business problem into a science problemYou will define methods for data collection and performance evaluationYou will experiment new models and evaluate their performanceYou will perform deep dive to understand potential issues impacting model performance, and form hypotheses for improvementYou will help deploy the model into productionYou will communicate your experimental and production result to Product Managers and business stakeholders
US, Virtual
Job summaryThe AWS Activate Program provides startups the resources they need to grow successfully on AWS. We do this by understanding the uniqueness of each and every startup that applies for Activate, and then personalizing the resources we make available to them. Our resources include (but are not limited to) AWS service credits, Business Support credits, technical education and training, opportunities for business and technical mentorship from Amazonians and startup peers, and personalized growth benefits. The Activate Personalization Team is the brains behind the Activate system. This team is responsible for ingesting startup data from multiple internal and external services, aggregating it into a holistic startup profile, and creating and productionizing ML models. Our team is looking for an experienced Data Scientist (DS) with outstanding leadership skills and the proven ability to build and manage medium-scale modeling projects. The candidate will be an expert across multiple data science domains including data transformation, machine learning, and statistics. Key job responsibilitiesResearch cutting edge algorithms, develop new models, and design and run experiments to improve customer personalizationPartner with scientists, engineers and product leaders to solve business and technology problems using scientific approaches to build new services that surprise and delight our customersCollaborate with BI/Data Engineer teams and drive the collection of new data and the refinement of existing data sources to continually improve data qualityPropose and validate hypothesis to deliver and direct our product road mapConstructively critique peer research and mentor junior scientists and engineers
US, NY, New York
Job summaryWe are open to candidates located in:Seattle, WashingtonPalo Alto, CaliforniaArlington, VirginiaKey job responsibilitiesAs a Senior Research Scientist, you will:Research and develop new methodologies for demand forecasting, alarms, alerts and automation.Apply your advanced data analytics, machine learning skills to solve complex demand planning and allocation problems.Work closely with stakeholders and translate data-driven findings into actionable insights.Improve upon existing methodologies by adding new data sources and implementing model enhancements.Create and track accuracy and performance metrics.Create, enhance, and maintain technical documentation, and present to other scientists, engineers and business leaders.Drive best practices on the team; mentor and guide junior members to achieve their career growth potential.A day in the lifeAbility to utilize exceptional modeling and problem-solving skills to work through different challenges in ambiguous situations.You’ve successfully delivered end-to-end operations research projects, working through conflicting viewpoints and data limitations.You have an enviable level of attention to details.Ability to communicate analytical results to senior leaders, and peers.Innovative scientist with the ability to identify opportunities and develop novel modeling approaches in a fast-paced and ever-changing environment, and gain support with data and storytelling.About the teamVideo advertising is a complex, multi-sided market with many technologies at play within the industry. The industry is rapidly growing and evolving as viewers are shifting from traditional TV viewing to OTT, and from terrestrial radio to streaming. In addition, publishers are increasingly adding video content to their online experiences. Amazon’s video advertising program is a rising competitor in this industry. Amazon’s service has differentiated assets in our customer & audience insights, exclusive video content and associated inventory on our streaming services (IMDbTV, Twitch, Prime Video, Amazon Music, etc.) and devices (FireTV, Echo, Fire Tablet) which all position us well as an end to end service for advertisers and agencies. As our business grows, we are continually experimenting with a portfolio of emerging ideas and technology as well as global expansion. We are looking for passionate, hard-working, and talented individuals to help foster these nascent ideas into scalable products and launch them into the market.