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.

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.
IN, TS, Hyderabad
Job summaryAre you excited about driving business growth for millions of sellers by applying Machine Learning? Do you thrive in a fast-moving, large-scale environment that values data-driven decision making and sound scientific practices? We are looking for experienced data scientists to build sophisticated decision making systems that help Amazon Marketplace Sellers to grow their businesses.Amazon Marketplace enables sellers to reach hundreds of millions of customers and provides sellers the tools and services needed to make e-commerce simple, efficient and successful. Our team builds the core intelligence, insights, and algorithms that power a range of products used by millions of sellers. We are tackling large-scale, challenging problems such as helping sellers to prioritise business tasks by bringing together petabytes of data from sources across Amazon.You will be proficient with creating value out of data by formulating questions, analysing vast amounts of data, and communicating insights effectively to audience of varied backgrounds. In addition, you'll contribute to online experiments, build machine learning pipelines and personalised data products.To know more about Amazon science, Please visit https://www.amazon.scienceKey job responsibilities· Collaborate with domain experts, formulate questions, gather, process and analyse petabytes of data to unearth reliable insights· Design & execute experiments and analyze experimental results· Communicate insights effectively to audience of a wide range of backgrounds· Formulate relevant prediction problems and solve them by developing machine learning models· Partner with data engineering teams to improve quality of data assets, metrics and insights· Leverage industry best practices to establish repeatable science practices, principles & processes
US, CA, Santa Clara
Job summaryJob 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, WA, Seattle
Job summaryWorkforce Staffing (WFS) brings together the workforce powering Amazon’s ability to delight customers: the Amazon Associate. With over 1M hires, WFS supports sourcing, hiring, and developing the best talent to work in our fulfillment centers, sortation centers, delivery stations, shopping sites, Prime Air locations, and more.WFS' Funnel Science and Analytics team is looking for a Research Scientist. This individual will be responsible for conducting experiments and evaluating the impact of interventions when conducting experiments is not feasible. The perfect candidate will have the applied experience and the theoretical knowledge of policy evaluation and conducting field studies.Key job responsibilitiesAs a Research Scientist (RS), you will do causal inference, design studies and experiments, leverage data science workflows, build predictive models, conduct simulations, create visualizations, and influence science and analytics practice across the organization.Provide insights by analyzing historical data from databases (Redshift, SQL Server, Oracle DW, and Salesforce).Identify useful research avenues for increasing candidate conversion, test, and create well written documents to communicate to technical and non-technical audiences.About the teamFunnel Science and Analytics team finds ways to maximize the conversion and early retention of every candidate who wants to be an Amazon Associate. By focusing on our candidates, we improve candidate and business outcomes, and Amazon takes a step closer to being Earth’s Best Employer.
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, VA, Arlington
Job summaryAmazon is investing heavily in building a world class advertising business and we are responsible for defining and delivering a collection of self-service performance advertising products that drive discovery and sales. Our products are strategically important to our Retail and Marketplace businesses driving long term growth. We deliver billions of ad impressions and millions of clicks daily and are breaking fresh ground to create world-class products. We are highly motivated, collaborative and fun-loving with an entrepreneurial spirit and bias for action. With a broad mandate to experiment and innovate, we are growing at an unprecedented rate with a seemingly endless range of new opportunities.Sponsored Products helps merchants, retail vendors, and brand owners succeed via native advertising that grows incremental sales of their products sold through Amazon. The Sponsored Products Ad Marketplace organization optimizes the systems and ad placements to match advertiser demand with publisher supply using a combination of machine learning, big data analytics, ultra-low latency high-volume engineering systems, and quantitative product focus. Our goals are to help buyers discover new products they love, be the most efficient way for advertisers to meet their business objectives, and to build a major, sustainable business that helps Amazon continuously innovate on behalf of all customers.We are seeking a Sr. 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 team, Machine Learning and Deep Learning technologies including Semantic Retrieval, Natural Language Processing (NLP), Information Extraction, Image Understanding, Learning to Rank are used to match shoppers' search queries to ads with per impression prediction models that run in real-time with tight latency budgets. Models are trained using self-supervised techniques, transfer learning, and supervised training using labeled datasets. Knowledge distillation and model compression techniques are used to optimize model performance for production serving.The Senior Manager role will lead science and engineering efforts in these areas for Amazon Search pages WW. The person in this role is responsible for: maintaining the consistent and long term reliability for the models and the delivery services that power them, managing diverse teams across multiple domains, and collaborating cross-functional with other senior decision makers. Our critical LPs for this role are Think Big, Are Right A lot, and Earns Trust. What is key is that the leader will need a dynamic mindset to build systems that are flexible and will scale.In this role, you will:· Lead a group of both applied scientists 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.Locations: Seattle, WA; New York, NY; Arlington, VA
US, WA, Seattle
Job summaryAmazon Sub-Same-Day Supply Chain team is looking for an experienced and motivated Senior Data Scientist to generate data-driven insights influencing the long term SSD supply chain strategy, build the necessary predictive models, optimization algorithms and customer behavioral segments allowing us to discover and build the roadmap for SSD to enable operational efficiency and scale.Key job responsibilitiesWork with product managers, engineers, other scientists, and leadership to identify and prioritize complex problems.Translate business problems into specific analytical questions and form hypotheses that can be answered with available data using scientific methods or identify additional data needed in the master datasets to fill any gapsDesign, develop, and evaluate highly innovative statistics and ML modelsGuide and establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementationProactively seek to identify business opportunities and insights and provide solutions to shape key business processes and policies based on a broad and deep knowledge of Amazon data, industry best-practices, and work done by other teams.A day in the lifeIn this role, you will be a technical expert with significant scope and impact. You will work with Product Managers, Business Engineers, and other Scientists, to deeply understand SSDs current optimization strategy while benchmarking against industry best practices and standards to gain insights that will drive our roadmap. A successful Data Scientist will have extreme bias for action needed in a startup environment, with outstanding leadership skills, proven ability to build and manage medium-scale modeling projects, identify data requirements, build methodology and tools that are statistically grounded. It will be a person who enjoys diving deep into data, doing analysis, discovering root causes, and designing long-term scientific solutions. We are seeking someone who can thrive in a fast-paced, high-energy and fun work environment where we deliver value incrementally and frequently. We value highly technical people who know their subject matter deeply and are willing to learn new areas. We look for individuals who know how to deliver results and show a desire to develop themselves, their colleagues, and their career.About the teamAmazon's Sub-Same Day (SSD) delivery program is designed to get customers their items as fast as possible – currently in as quickly as five hours. With ultra-fast delivery becoming increasingly important, we are looking for an experienced Senior Data Scientist to help us benchmark against industry standards to uncover insights to improve and optimize the long term supply chain strategy for Amazons Sub-Same-Day business.
US, WA, Seattle
Job summaryAmazon's Weblab team enables experimentation at massive scale to help Amazon build better products for customers. A/B testing is in Amazon's DNA and we're at the core of how Amazon innovates on behalf of customers. We are seeking a skilled Applied Scientist to help us build the future of experimentation systems at Amazon.About you:You have an entrepreneurial spirit and want to make a big impact on Amazon and its customers. You are excited about cutting-edge research on unsupervised learning, graph algorithms, and causal inference in the intersection between Machine Learning, Statistics, and Econometrics. You enjoy building massive scale and high performance systems but also have a bias for delivering simple solutions to complex problems. You're looking for a career where you'll be able to build, to deliver, and to impress. You challenge yourself and others to come up with better solutions. You develop strong working relationships and thrive in a collaborative team environment.About us together:We're going to help Amazon make better long term decisions by designing and delivering A/B-testing systems for long-term experiments, and by using these systems to figure out how near term behavior impacts long term growth and profitability. Our work will inform some of the biggest decisions at Amazon. Along the way, we're going to face seemingly insurmountable challenges. We're going to argue about how to solve them, and we'll work together to find a solution that is better than each of the proposals we came in with. We'll make tough decisions, but we'll all understand why. We'll be the dream team.We have decades of combined experience on the team in many areas science and engineering so it's a great environment in which to learn and grow. A/B testing is one of the hottest areas of research and development in the world today and this is a chance to learn how it works in the company known for pioneering its use.
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.