Amazon Glamazon Gay Pride Month LGBTQIA+ Black Lives Matter
From top left to bottom right: Luyolo Magangane, applied scientist; Ruiwei Jiang, research scientist; Sheeraz Ahmad, applied scientist; Liz Dugan, user experience researcher; Shane McGarry, data scientist; Abhinav Aggarwal, applied scientist.
Credit: Glynis Condon

Pride and prejudice: 6 Amazon scientists share their experiences

Scientists from glamazon, Amazon’s LGBTQIA+ affinity group, say this year's Pride Month is as much about solidarity as it is about celebration.

In most cities around the world June is considered Pride Month, where people celebrate diversity and inclusion. It usually culminates in a parade or march to promote the self-affirmation, equality, and visibility of the lesbian, gay, bisexual, transgender, queer or questioning, intersex, and asexual or allied (LGBTQIA+) community.

At Amazon, it's no different. There's a community of more than 7,000 employees from across the globe who are part of glamazon, an affinity group and employee network, whose mission is to connect those interested in LGBTQIA+ issues to company resources and to each other and to showcase Amazon’s acceptance in communities worldwide.

Given current events, particularly global protests resulting from the videotaped killing of George Floyd by law enforcement officials and the recent U.S. Supreme Court ruling upholding LGBTQIA+ equality, we asked some of the scientists within this affinity group about the significance of this year’s Pride Month.

Abhinav Aggarwal, applied scientist, Alexa Trust

Abhinav Aggarwal (pronouns: he/him/they/them) joined Amazon about nine months ago, after obtaining his PhD in computer science from the University of New Mexico in 2019. His work focuses on building customer trust by designing privacy-preserving machine learning algorithms for handling customer data.

Abhinav Aggarwal, applied scientist, Alexa Trust
Abhinav Aggarwal, applied scientist, Alexa Trust

“Since I joined Amazon, I’ve only had a very passive interaction with glamazon through emails. But I feel like the variety of topics discussed there is absolutely amazing. It’s not just LGBTQIA+ issues; there are thoughts about body positivity, gender pronouns, having pronouns on badges, and issues around diversity and inclusion,” he said.

“But I’d like to see more gender-neutral restrooms in the buildings and use of the ‘they’ pronoun by default,” he says. “Whenever I refer to someone I don’t personally know or even know of at all, I default to using ‘they/them’ as a pronoun. It would be nice to see this as common practice and not assuming someone’s gender based on familiarity with the name, which aligns with the removal of unconscious bias and helps with acceptance.”

With privacy and fairness in AI becoming an increasingly important topic, Aggarwal sees similar issues within his field.

“You don’t want your models for services like Alexa to give you results that are gender-biased, especially as we move towards a more gender-neutral world,” Aggarwal explains. “Ideally, our models should produce gender-agnostic results, and we must work backwards from this goal when defining gender-based fairness. That’s something I’ve felt a lot of pushback with within the industry, because the problem becomes far more complex if you talk about gender neutrality and the continuous spectrum of gender, instead of just the binary male or female.”

Aggarwal sees celebrating Pride Month as a step towards this awareness.

“I think these movements are absolutely necessary because they call out basic human rights against discrimination. They call out a very fundamental way of how we think we should be treated. LGBTQIA+ is a tag to help identify and understand ourselves better. It doesn’t change who we are as a person. It doesn’t change how technically advanced or skilled we are. It doesn’t change how we are going to perform at Amazon,” Aggarwal emphasizes.

“If the person is a good human being at heart, helps society and contributes to the general well-being of the nation, that’s what’s more important, independent of whether they are gay, lesbian, Black, white or associate themselves in any other way. Acknowledgement of this label-agnostic human existence is much more than man-made tags.”

Sheeraz Ahmad, applied scientist, Amazon SageMaker Ground Truth

Sheeraz Ahmad (pronouns: he/him) joined Amazon more than four years ago as a research scientist. Today, he works as an applied scientist on Amazon SageMaker Ground Truth team, an AWS data-labeling service that makes it easy to build highly accurate training data sets for machine learning.

Sheeraz Ahmad, applied scientist, Amazon SageMaker Ground Truth
Sheeraz Ahmad, applied scientist, Amazon SageMaker Ground Truth

Prior to Amazon, he received his PhD in computer science from the University of California San Diego (UCSD), where he focused on computational modeling of human and animal behavior in different domains, with the goals of gaining insights into the inner workings of the brain and developing behaviorally inspired machine learning models.

Ahmad, who grew up in Kanpur, India, previously earned his bachelor’s degree in electrical engineering from the prestigious Indian Institute of Technology Kanpur.

In Kanpur, Ahmad's experience was that being on the LGBTQIA+ spectrum was not well accepted, and he didn’t have many role models to follow. That changed after college when he moved to a larger city, Bangalore, and especially when he attended UCSD, where “I came across people who were out and proud and doing amazing things in life.”

Now, as an active member of Amazon’s glamazon affinity group, Ahmad is a role model himself. When he first joined Amazon, he appreciated glamazon’s support and attended events but found socializing difficult in some of the larger events. So for more than four years now, he’s organized monthly game nights, where a smaller group of glamazon members in Seattle get together to socialize and play board games. Even during the COVID-19 pandemic the tradition has continued, though online.

Pride Month is especially meaningful to Ahmad, but this year “the tone is more somber, understandably so.”

“There’s a lot going on, and as much as there is to celebrate, there’s so much more to be done. This month, as a gay man, my focus is more on being an ally for people who are going through their own struggles,” he says. “Gay men have faced discrimination and hardship, and we need to lean into those experiences, remember all the pain we’ve gone through, and be there for the womxn and our African-American brothers and sisters.

“I’m sharing with my friends, who tend to be somewhat conservative, how I have felt, based on my own experiences, and trying to relate how all members of the LGBTQIA+ community are feeling now, especially those who are African American. It’s important to be there for them, to be an ally, providing solidarity.”

“This year," Ahmad says, “feels less about celebration and more about solidarity.”

Liz Dugan, user experience researcher, Amazon Alexa

Liz Dugan (pronouns: she/her) joined Amazon earlier this year and during her onboarding experience learned about the glamazon affinity group. The voice user interface researcher, who earned a bachelor’s degree in psychology and a master’s degree in cognitive psychology from the University of Oklahoma, self-identifies as a queer, bisexual woman. She immediately felt welcomed by glamazon members.

Liz Dugan, user experience researcher, Amazon Alexa
Liz Dugan, UX researcher, Amazon Alexa

“Since I’ve been here, I’ve noted more and more people joining the group, and everyone is treated the same. People reach out and say, ‘How can we help you? Is there anything we can provide you? Please let us know if there’s anything you need.’ So you immediately feel as though this is a safe place.”

On this day, despite recent events, Dugan is more upbeat, as the Supreme Court has just ruled that a landmark civil-rights law protects gay and transgender workers from workplace discrimination. “An employer who fires an individual merely for being gay or transgender defies the law,” Justice Neil M. Gorsuch wrote for the majority in the court’s 6-to-3 ruling.

“So the LGBTQIA+ community just had a very historic win today. We wouldn’t be experiencing the moment we are today without Stonewall,” she says, referring to the 1969 New York City Stonewall riots that are considered one of the most important events leading to today’s fight for LGBTQIA+ rights.

“Everything we have today started with Stonewall, which was a riot started by trans people of color. So today we can live publicly and authentically and mostly safe from verbal abuse because of Black trans activists. Yet today we are still seeing those same populations being actively targeted and murdered without any real recourse or much publicity. Just within the past few days two Black trans women were murdered, and I’ve seen no one talk about it.”

“Some of the freedoms we enjoy today are because of Black trans women, and yet we continue to fail them as a privileged group of gay mostly white individuals, and we’re not doing enough to support the Black Lives Matter movement now. …We need to return to our roots and lift up our brothers and sisters who are suffering. They started the movement for us, and we need to be there for them now.”

Like other colleagues, Dugan feels like this year’s Pride Month is less a time to celebrate and more a time to continue pushing for progress.

“It’s a moment to return to our community’s roots. We still have problems,” she says. “We still have youth who don’t have homes and are struggling; we still have people who are discriminated against; we still have people who are being brutalized and murdered. So while we can be proud of what we’ve accomplished, we still have work to do. We have to carry our pride but still get our hands dirty. Stonewall wasn’t a celebration. Stonewall was a riot. So we have to keep fighting.”

Ruiwei Jiang, research scientist, Alexa Domains - HHO

Before joining Amazon as a research scientist, Ruiwei Jiang (pronouns: she/her) studied computational genetics in college, working in particular on human DNA. Her studies explored the adverse impact of pollution on human genetic encoding, comparing the short- and long-term effects of living in a polluted versus non-polluted environment.

Ruiwei Jiang, research scientist, Alexa Domains
Ruiwei Jiang, research scientist, Alexa Domains

“It might not sound super relevant to Alexa, but you're doing computation decks, working with a lot of data, writing code and doing a lot the analysis and building out of models, so that sort of became transferable knowledge,” she says.

Her role within the Alexa Household Organization, whose mission is to help Alexa help families stay organized and connected with one another, is to maintain the natural-language-understanding framework for features such as reminders, calendar tasks, weather, and recipes, as well as for creating models to improve customer retention.

“The world is moving towards conversational AI,” she says, “and it’s cool to be able to say you’re working in this field and developing models that are actually being used by customers, who are directly benefiting from it.”

Jiang is based in Amazon’s Vancouver office, where she’s experienced many positive actions from the glamazon affinity group, which have warmed her heart.

“They organize meetings in the office on a Sunday afternoon or Saturday morning, before the Pride parade, and hand out stickers. It’s a small thing, but it all adds up. Previous companies I’ve worked at have never really stood up as a corporation and been like ‘hey, we’re going to do something together for the Pride parade’. But at Amazon, it’s like ‘hey, let’s get together and show our support and be part of the community’, which is really inspiring.”

As a self-proclaimed ally, she can relate to the LGBTQIA+ community. “Growing up in Canada as a Chinese Canadian, I know how it feels to be to be left out and stigmatized and not feel like you're part of the group, or welcome. So I can imagine how other groups of people feel, even if I don’t have full visibility into all the problems and discrimination that they face. I think it’s important to stand up for what I think is right and not just have those values and keep it to myself.”

In light of recent events, she’s been impressed by the top-down communication at Amazon, from vice president to director level, with each leader taking the time to listen to employees and expressing their views that what’s happening to Black people in the U.S. isn’t right.

“We need to make the workplace more human than it is right now. We spend eight hours a day here, and we make friends. It’s also about keeping that diversity in hiring, which I think is one of the best ways to break down barriers, by having cross-community, cross-culture, cross-gender friendships and communications.”

Mentoring is another way Jiang promotes diversity and inclusion. “I’m what they call ‘women in tech’, and I’ve been in my career for about six years, so I think it’s important to mentor other women and girls, so they don’t feel left out or scared.”

Luyolo Magangane, applied scientist, Amazon Elastic Compute Cloud (EC2)

Located in South Africa, Luyolo Magangane (pronouns: he/him) joined Amazon just over a year ago, after a friend referred him for a machine learning role.

Luyolo Magangane, applied scientist, Amazon Elastic Compute Cloud (EC2)
Luyolo Magangane, applied scientist, Amazon Elastic Compute Cloud (EC2)

“I’m in the placement team, and we try to help customers have the best experience possible whenever they use AWS. So if a customer launches an EC2 instance, my team is in charge of the decision-making algorithm that chooses where to place that instance,” he explains.

Prior to Amazon, he studied electrical and computer engineering at the University of Cape Town and obtained a master’s degree in artificial intelligence at Stellenbosch University. He had a few jobs within the industry before joining Amazon.

He’s a member of Amazon’s glamazon affinity group, where he identifies as an ally and believes it’s important that others do too.

“Everyone should believe in the respect of the humanity of people first. When you meet someone, you have no context of their background or how they grew up. The only thing you know is that you are human, and they're also human. Your sexual orientation, gender identity, or racial identity doesn’t matter. It becomes much harder to be bigoted and to oppress someone if everyone starts from that perspective,” he says.

Magangane believes his support for the LGBTQIA+ community stems from his childhood, during which South Africa saw the end of apartheid, a system of institutionalized racial segregation from 1948 until the early 1990s.

“That was when [Nelson] Mandela was released from prison. That was when you could see the tides of change coming, from minority rule to democracy, which was incredible,” he explains.

“Every day I was encouraged to dream. And so, the benefit of being born in an environment like that led to me being born very free of prejudice. But because, historically, I come from a somewhat conservative background, I have a lot of friends and family who I care about who aren't as open minded as I think they could be.”

When he thinks about Pride and the Black Lives Matter movement and what society can learn from these events, he quotes Killer Mike, an American rapper, songwriter, actor, and activist: “It’s to ‘strategize, organize, and mobilize’, peaceful protests. It’s always done through people organizing, coming out, being peaceful, and saying that we believe what's happened is wrong and things need to change,” he says.

“I think part of that is not tolerating bigotry, which is one of the challenges you have to deal with in the Black community. You’re taught to pick and choose your battles, but you end up tolerating all those things that you don't battle, which only encourages it. You have to look bigotry in the eye and demand change. You cannot tolerate any of that. Even if institutions have to change, we’re demanding the change now.”

Shane McGarry, data scientist, Amazon Fashion

Shane McGarry (pronouns: they/them) joined Amazon earlier this year as a data scientist, focused on improving the company’s fashion catalogue using machine learning and other techniques “to create a stellar experience for our customers.”

Shane McGarry, data scientist, Amazon Fashion
Shane McGarry, data scientist, Amazon Fashion

McGarry, who identifies as non-binary, meaning they (McGarry prefers the pronouns they/them to he/she, thus the use of their, they, and them in this section) don’t exclusively identify as a man or a woman, recently earned their PhD in computer science from Maynooth University, about 25 minutes outside Dublin, Ireland, where their thesis work focused on improving the search experience within digital research environments (historical records, etc.) through visual search techniques.

Before joining Amazon, McGarry held several software development roles, where they encountered challenges.

“I’m non-binary, and I’m not traditionally masculine in any way shape or form, from my speech patterns to the way I carry myself,” McGarry explains. “What I found is that I was often ignored in ways that my colleagues with the same level of experience weren’t. When working with clients, if I dealt with them over email, they were receptive to my ideas, but when we started talking over the phone and they would hear my voice, suddenly they would become skeptical of what I was saying.”

McGarry says they encountered similar challenges with management.

“There were a lot of times when my opinion was brushed to the side, despite being proven consistently right. I would say ‘I see a problem; I think we should do this differently.’ They would ignore me, and no matter how many times I was proven right, I was never taken seriously.”

Affinity groups and diversity at Amazon

After joining Amazon, McGarry became involved in glamazon, one of 12 affinity groups within the company aimed at bringing employees together across businesses and locations around the globe. They’ve been impressed with glamazon and with their organization’s response to recent events related to the killing of George Floyd and how it’s recognizing Pride Month.

“The management within Amazon Fashion has really impressed me, especially within the past few weeks with everything that’s been occurring. …The president of our business had an all-hands meeting where she invited a global diversity and inclusion leader who has dealt with racial trauma. She talked to us about racial trauma, what it is, and how it affects people.”

Asked about lessons we can derive from recent current events, McGarry says, “In terms of the Black Lives Matter movement, it’s really important for us as individuals, as well as the company as a whole, to examine our racial biases that result from growing up in a culture that favors white people. Having a racial bias doesn’t make you a bad person. But refusing to acknowledge it, to examine it, and to work towards unlearning it, that’s where the problem lies.”

McGarry, who grew up in northeast Ohio within a deeply religious family, understands firsthand the challenges of dealing with bias and prejudice. For McGarry, Pride Month represents an opportunity to celebrate who they are without fear.

“As someone who grew up in the eighties and nineties in a deeply religious home where being gay wasn’t acceptable, and hearing messages from the community and church that gay people are evil, that God hates them, you get inundated with all of these negative messages, and you really begin to hate yourself, who you are, and you live in constant fear. So for me, Pride Month is about letting a lot of that go and celebrating yourself for who you are and really embracing it. At the same time, we have to remember our history, how far we’ve come, but yet how far we still need to go.”

Read more stories like this in our Working at Amazon section, or take a look at some of our available career opportunities in science.


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Prime Video is shaping the future of digital video entertainment. Our mission is to build the widest selection of digital video content and make it easy for customers to stream wherever and whenever they want. The Video Personalization team’s mission is to give customers individual Video recommendations, to surface the titles that they will most enjoy watching.As a Data Scientist in the Video Personalization team, you will play a vital role in understanding how to optimize the customer experience, and how to measure and recognize long term customer value. Your insights will drive what the Personalization product engineering team invests in, and help set and measure annual goals.In this role, you will own measurement strategy, weblab A/B training and office hours, performance tracking, whilst developing new insightful metrics and scaling the existing customer ML models that help define success within online A/B tests. You will work closely with the director, senior managers, product managers, engineers and ML specialists in the Personalization team, as well as people across Video and Amazon in finance, merchandising and economist teams.The successful candidate for this position will understand customers and business problems, and being a skilled modeler will be able to go complex or simple as appropriate. The role will include:- Using R, Python, Sagemaker/Eider, Redshift to analysis and model huge quantities of data- Work with product leaders to understand and reshape their customer problems and deliver innovative solutions- Own a problem space end to end and deliver to agreed timelines- Deep dive experiments to better shape the next set of treatments- Create new metrics that will help guide and evaluation specific customer experience.- Understand how best to cohort customers to track and optimize customer journeys.
US, WA, Bellevue
The Global Delivery Services (GDS) organization strives to deliver packages to Amazon’s customers with fast and reliable delivery speeds at the lowest cost. Providing a high quality delivery service requires a carefully optimized outbound transportation network design that makes the right tradeoffs between cost, speed and DEA in order to maximize the Long-term Free Cash Flow (LTFCF).The NA-Customer Delivery Excellence (CDE) team within the GDS org uses machine learning, econometrics, and data science to identify opportunities for Amazon’s NA Transportation network with an objective to enhance Amazon’s ability to deliver packages to customers in faster, cheaper and reliable manner. We generate insights to guide long term strategy as well as provide short and medium term plans for our execution teams. We use detailed customer ordering data (eg: location, frequency) and detailed information about the fulfillment process (inventory placement, capacities, SLAs, on-time performance) to predict and understand the delivery speed and quality we are offering to our customers.We are looking for a motivated Data Scientist to build, optimize and productize cutting edge machine learning models. A successful candidate will have strong quantitative, data mining, statistical modeling, machine learning skills and is comfortable facilitating ideation and working from concept through to execution. The position will partner with Engineering, Supply Chain teams, Finance and Technology teams to enhance short term and long term predictions that use a range of data science methodologies to automate data analysis or to solve complex business problems for the NA Transportation network.Responsibilities include building automated tools and support structures needed to analyze data, design metrics for complex systems, dive deep to determine root cause of forecast errors & changes, create statistical definition of the outliers and methodologies to systematically identify and mitigate model variance drivers.A qualified candidate must have demonstrated ability to develop and manage medium to large-scale models and methodologies that are statistically grounded but also functional and practical. Must possess strong written and verbal communication skills, proven ability to engage and collaborate with customers to drive improvements. Possess high intellectual curiosity with ability to quickly learn new concepts/frameworks, algorithms and technology. Key responsibilities of CDE data scientists include the following:· Research machine learning algorithms and implement by tailoring to particular business needs and test on large datasets.· Manipulating/mining data from databases (Redshift, SQL Server, Oracle DW) and create automated metrics using complex databases· Collaborate with BI/Data Engineer teams and drive the collection of new data and the refinement of existing data sources to continually improve data quality· Helping build production grade systems to support decision making with an objective of optimizing the network design to improve customer experience and grow the Amazon business.· Improving model usability by analyzing customer behavior and by gathering requirements from business owners and other tech teams. Incorporating new data sources and implementing creative methodologies to improve model performance.· Creating and tracking accuracy and performance metrics. Root cause and research process breakdowns· Foster culture of continuous engineering improvement through mentoring, feedback, and metrics
US, WA, Seattle
Are you excited to be a member of a new science and analytics team?Are you passionate to generate insights using scientific solutions?Are you the one who is full of ideas?The Customer Behavior Analytics (CBA) Org builds products from the ground up to serve internal teams. Products we developed include Downstream Impact (DSI) framework, Customer Targeting applications, and A/B testing platforms. We use cutting edge technologies that fuse Big Data with concepts from Machine Learning, Economics, and Data Science. These innovations help make strategic investment decisions and define the customer engagement metrics by which Amazon runs its business globally.The High Value Message (HVM) Analytics team within CBA is looking for an Applied Scientist to make an impact on how Amazon influences our shopper's perception. You will work with distributed machine learning and statistical algorithms across multiple platforms to harness enormous volumes of online data at scale to match customers and products/offers based on probabilistic reasoning. Our primary partners are Cross Channel Marketing and Digital Corporate Advertising team. A successful Applied Scientist has an entrepreneurial spirit and want to make a big impact on Amazon and our shoppers. You are excited about cutting-edge research on Deep Learning, Natural Language Processing (NLP), causal inference, and experimental design. You enjoy building massive scale and high-performance systems but also have a bias for delivering simple solutions to complex problems. We are looking for a thought leader and you demonstrate this by deploying solutions into production, not just by having ideas. We encourage you to challenge yourself and others to come up with better solutions. You will develop strong working relationships and thrive in a collaborative team environment. You need to be fluid in:AWS services (e.g. EMR, s3).Feature extraction, feature engineering and feature selection.Machine learning, statistical algorithms and recommenders.Model evaluation, validation and deployment.Casual Inference.Experimental design and testing.
US, CA, Sunnyvale
Are you inspired by invention? Is problem solving through teamwork in your DNA? Do you like the idea of seeing how your work impacts the bigger picture? Answer yes to any of these and you’ll fit right in here at Amazon. We are a smart team of doers that work passionately to apply cutting edge advances in robotics and software to solve real-world challenges that will transform our customers’ experiences in ways we can’t even imagine yet.As a Manager, Applied Science, you will wear many different hats and work on multiple components of the entire system, in a highly collaborative environment that’s more startup than big company. You will tackle problems that span a variety of domains: computer vision, image recognition, machine learning, real-time and distributed systems.You will also help in defining the creative vision, product requirements, and user experience for this robotics program. Working with a cross-disciplinary team of analysts, designers, hardware engineers, and researchers, you will define and drive the product from concept all the way through to production.You should be a self-starter with a bias towards independent problem solving. Clear communication and prioritization will be important as you plan, design, and deliver the best experience for millions of customers. Your passion for the potential of using technology to improve people’s lives, and your experience leading complex technology projects will help you make strong business judgments.If you’re entrepreneurial and want to build and own transformative technology-driven products, join us in making history.As a part of this role, you will:· Lead the design and implementation of a cutting-edge technology in the Robotics space, focusing on SLAM.· Build and manage a team of Scientists.· Foster career growth and a strong team culture.· Recruit, hire, mentor, and coach technical staff.· Interface with our internal customers to understand requirements, set priorities and communicate direction and progress.· Own all operational metrics and support for your team.· Manage the agile development process and methodology to deliver incremental value to customers.· Help develop long-term roadmaps and business technology strategies.
US, WA, Seattle
Ever wonder how you can keep the world’s largest selection also the world’s safest and legally compliant selection? Then come join a team with the charter to monitor and classify the billions of items in the Amazon catalog to ensure compliance with various legal regulations.Our mission is to enable business users to self-serve build, deploy, maintain and improve prod cut classifiers at Amazon catalog scale. To enable this mission, one needs an ecosystem that proactively interacts and assists its users in delivering a robust ML solution. A self-serve product classification system that proactively engages with its user in a near real-time fashion by providing intuitive “insights and biases” about a model’s learning and seeks user feedback enabling continuous re-learning and correction.In this role, you will have an opportunity to lead state of the art machine learning algorithms on large datasets. You will need to lead & build Amazon scale applications running on Amazon Cloud that both leverage and create new technologies to process large volumes of data that derive patterns and conclusions from the data.We are seeking an Applied Science Manager who has a solid background in applied Machine Learning and AI, deep passion for building data-driven products; ability to communicate data insights and scientific vision, and has a proven track record of leading both applied scientists and software engineers to execute complex projects and deliver business impacts.In this role, you will:· Lead a group applied scientists (predominantly) and software engineers to deliver machine-learning and AI solutions to production.· Advance team's engineering craftsmanship and drive continued scientific innovation as a thought leader and practitioner.· Develop science and engineering roadmap, run Sprint/quarter and annual planning, and foster cross-team collaboration to execute complex projects.· Perform hands-on data analysis, build machine-learning models, run regular A/B tests, and communicate the impact to senior management.· Hire and develop top talents, provide technical and career development guidance to both scientists and engineers in the organization.
US, WA, Seattle
How many FireTV devices should Amazon build?If you're interested in using science to answer critical business questions like this, Amazon Devices Demand Planning is the place to be. We develop scalable and robust state-of-the-art forecasting solutions for the entire portfolio of Amazon devices. As a scientist on the team, you will have an opportunity to both develop advanced scientific solutions and drive critical customer and business impacts. You will play a key role to drive end-to-end solutions from understanding our business requirements, exploring a large amount of historical data, building prototypes and exploring conceptually new solutions. You will collaborate closely with peers in engineering as well as business stakeholders. You will be at the heart of a growing and exciting focus area for Amazon Devices.Key responsibilities:· Research and develop new methodologies for demand forecasting.· Improve upon existing methodologies by adding new data sources and implementing model enhancements.· Drive scalable solutions.· Create and track accuracy and performance metrics (both technical and business 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.
US, WA, Seattle
Are you passionate about conducting measurement research and experiments to assess and evaluate talent? Would you like to see your research in products that will drive key talent management behaviors globally to ensure we are raising the bar on our talent? If so, you should consider joining the Global Talent Management (GTM) Science Team!Amazon GTM Science team is an innovative organization that exists to propel Amazon HR toward being the most scientific HR organization on earth. The GTM Science mission is to use Science to assist and measurably improve every talent decision made at Amazon. GTM Science does this by discovering signals in workforce data, infusing intelligence into Amazon’s talent products, and guiding the broader GTM team to pursue high-impact opportunities with tangible returns. This multi-disciplinary approach spans capabilities, including: data engineering, reporting and analytics, research and behavioral sciences, and applied sciences such as economics and machine learning.We are seeking Assessment and Measurement Scientists with expertise developing assessment and validating measures (assessments, performance evaluations, and surveys) to evaluate talent at Amazon. This person will possess knowledge of different assessment approaches to evaluate performance, a strong psychometrics background, scientific survey methodology, computing various content validity analyses, and experience developing legally defensible talent evaluation programs. In this role you will:· Lead the global research strategy developing performance evaluations both quantitative and qualitative· Execute a scalable global content development and research strategy Amazon-wide· Conduct psychometrics analyses to evaluate integrity and practical application of content· Identify research streams to evaluate how to mitigate or remove sources of measurement error· Partner closely and drive effective collaborations across multi-disciplinary research and product teams· Manage full life cycle of large scale research programs (Develop strategy, gather requirements, execute, and evaluate)
US, WA, Seattle
Do you want to join a brand new team building an AI system that would disrupt the industry? Do you enjoy dealing with ambiguity and working on hard problems in a fast-paced environment?Amazon Connect is a highly disruptive cloud-based contact center that enables businesses to deliver engaging, dynamic, and personal customer service experiences. With Amazon Connect, you can create your own cloud-based contact center and be taking calls in minutes. Amazon Connect leverages the power of Artificial Intelligence and the large ecosystem of AWS services such as Lex, Transcribe, Lambda, S3, and Kinesis to provide a truly frustration free and natural customer experience. With this technology, we are transforming an industry and the way customers interact with businesses and how agents service them.As an Applied Scientist on our team, you will analyze data from huge data sets, create ML forecasting and classification models from conception to deployment, and work closely with other senior technical leaders within the team and across AWS. You will demonstrate your deep Applied Science knowledge and experience at prototyping and building accurate and effective ML models using technology such as AWS Sagemaker, PyTorch, and SparkML. Our team is at an early stage, so you will have significant impact on our ML deliverables with no operational load from existing models/systems.We have a rapidly growing customer base and an exciting charter in front of us that includes solving highly complex engineering and algorithmic problems. We are looking for passionate, talented, and experienced people to join us to innovate on this new service that addresses customer needs to build modern contact centers in the cloud. The position represents a rare opportunity to be a part of a fast-growing business soon after launch, and help shape the technology and product as we grow. You will be playing a crucial role in developing the next generation contact center, and get the opportunity to design and deliver scalable, resilient systems while maintaining a constant customer focus.Learn more about Amazon Connect here:https://aws.amazon.com/connect/
US, WA, Bellevue
Amazon's Customer Delivery Excellence team is looking for a motivated Data Scientist with proven ability to develop, enhance, automate, and manage optimization and cutting edge prediction and learning/Artificial Intelligence models using strong quantitative skills. The successful candidate will have strong data mining, statistical modeling, machine learning skills and is comfortable facilitating ideation and working from concept through to execution.The position will partner with Engineering, Supply Chain teams, Finance and Technology teams to enhance short term and long term volume prediction and optimization models that use a range of data science methodologies to automate data analysis or to solve complex business problems for the NA Transportation network. Responsibilities include building automated tools and support structures needed to analyze data, design metrics for complex systems, dive deep to determine root cause of forecast errors & changes, create statistical definition of the outliers and methodologies to systematically identify and mitigate model variance drivers.A qualified candidate must have demonstrated ability to develop and manage medium to large-scale models and methodologies that are statistically grounded but also functional and practical. Must possess strong written and verbal communication skills, proven ability to engage and collaborate with customers to drive improvements. Possess high intellectual curiosity with ability to quickly learn new concepts/frameworks, algorithms and technology.Additional Responsibilities include:· Research machine learning algorithms and implement by tailoring to particular business needs and test on large datasets.· Manipulating/mining data from databases (Redshift, SQL Server, Oracle DW)· Create automated metrics using complex databases· Providing analytical network support to improve quality and standard work results· Root cause research to identify process breakdowns within departments and providing data through use of various skill sets to find solutions to breakdown· Collaborate with BI/Data Engineer teams and drive the collection of new data and the refinement of existing data sources to continually improve data quality· Foster culture of continuous engineering improvement through mentoring, feedback, and metricsAmazon is an Equal Opportunity-Affirmative Action Employer- Female/Minority/Disability/Vet
UK, Cambridge
We are looking for someone who is excited to apply cutting-edge techniques from deep learning or natural language processing (NLP) to the text-to-speech (TTS) technology behind Alexa and our AWS cloud speech service.As a Machine Learning Scientist you will be responsible for leading the development and launch of core product features. You will have significant influence on our overall strategy by helping define these product features, drive the system architecture, and spearhead the best practices that enable a quality product.We believe that, like a human speaker, a text-to-speech system can produce more natural speech if it has an improved understanding of the meaning and context of the text. If you agree...You will have the opportunity to solve hard problems with voice – we’ve spent years of invention on this. When we started working on this, the technology didn’t even exist – we had to invent it. Join us if you want to apply your deep learning skills in a dynamic field that is revolutionising the way people interact with devices and services.We believe that voice will fundamentally improve the way people interact with technology. It can make the complex simple—it’s the most natural and convenient user interface. Voice is going to be a big part of our future and we are inventing it here.RESPONSIBILITIES· Use your expertise in deep learning to research and implement novel approaches to make improvements to our text-to-speech technology.· Lead and Mentor junior engineers and scientists.· Participate in the design, development, evaluation, deployment and updating of data-driven models and analytical solutions for spoken language applications.