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A grid of 12 women scientists who were asked what three steps we can take as a society to forge a more gender-equal science community
As International Women's Day approached, we asked women scientists from research areas across the company what three steps we can take as a society to forge a more gender-equal science community.
Credit: Glynis Condon
Sustainability

How to forge a more gender-equal science community

International Women's Day is March 8 with the theme: #ChooseToChallenge.

By Staff writer
March 4, 2021
9 min read
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International Women’s Day (IWD) is March 8, 2021. The day celebrates the social, economic, cultural and political achievements of women, and also denotes a call to action to accelerate gender parity. This year’s theme: #ChooseToChallenge.

International Women's Day logo

“From challenge comes change, so let’s all choose to challenge,” says the IWD website.

As IWD approached, Amazon Science asked women scientists from research areas across the company what three steps we can take as a society to forge a more gender-equal science community. Below are their responses.

Bouchra Bouqata

Bouchra is a senior applied scientist within Amazon Robotics. She earned her PhD in machine learning and artificial intelligence from Rensselaer Polytechnic Institute.

Bouchra Bouqata
Bouchra Bouqata

  • Provide a clear pipeline for advancing and promoting women’s careers in science. Companies and institutions should adopt gender-balanced peer review promotion processes and committees.  They should also provide special funds and grants to help women scientists further their research and work.
  • Conferences and publishing venues should adopt gender-conscious peer-review committee, and speaker- selection committee recruitment processes.
  • Companies and institutions should commit to educating everyone, not just leadership, to combat the issues facing women in science. They should provide gender awareness training as a standard component of any training they provide to their employees and members. They should provide seminars and convene roundtable discussions on gender issues in science to facilitate communication and identification of solutions.

Nilay Noyan Bulbul

Nilay is a principal scientist within the company’s Supply Chain Optimization Technologies organization.  She earned her PhD in operations research from Rutgers University.

Nilay Noyan Bulbul
Nilay Noyan Bulbul

  • Call the gender disparity out: Identify where women scientists are marginalized, and call out the disparity to ensure fair representation at the leadership of scientific research and decision-making, as well as “invite-only” prestigious roles, such as keynote speaking engagements, prize juries, and journal editorial board memberships.
  • Invest in the future: Create more initiatives and opportunities for the next generation of women scientists via mentoring and targeted prize and research fund calls.
  • Keep everyone accountable: Make sure every entity working towards gender equality in science community has a tangible way to measure the “change” and keep track of the progress, and make the process transparent.”

Cindy Cui

Cindy is a senior economist within the Alexa Shopping organization. She earned her PhD in economics from the University of Texas at Austin.  

Cindy Cui
Cindy Cui

Role models, aspirations, and supportive community are most important factors to me. Growing up, my grandma taught me reading and math. I still remember the days when we would go through math problems and I felt happy and proud when I solved them correctly.

My grandma is also one of the few female teachers in her generation and always emphasizes the importance of education and hard work. In school, many smart female classmates encouraged and challenged me throughout.

It takes all of us to improve gender equality in science, doing our best and helping others along the way.

Donna Dodson

Donna is a senior principal technologist within the AWS Security organization. She earned her master’s degree in computer science from Hood College.

Donna Dodson
Donna Dodson

  • Build a culture that values deep thinkers who balance speaking and listening to others. Often the subculture’s voices — including women’s — are not heard.
  • Create compensation, incentives, benefits, resources, recognition and a flexible workplace that balance needs at different stages in life. Early- and mid-career scientists with families require flexibility for a work-life balance.
  • Recognize and promote diverse voices throughout K-12 science programs to empower girls to grow their confidence in science knowledge, skills and abilities

Maryam Fazel-Zarandi

Maryam is a senior machine learning scientist within the Alexa AI organization. She earned her PhD in computer science at the University of Toronto.

Maryam Fazel-zarandi
Maryam Fazel-Zarandi
Credit: Pierce Harman Photography

I have been able to pursue my dream of becoming a scientist and have had access to role models and mentors throughout my education and career. The number of women scientists like me has increased over the past decades, however, we are still far from a gender equal science community.

While we should continue to reduce the large gap that still exists in terms of numbers, in my opinion, we should put more focus on mechanisms to retain women scientists. Lack of support for women in difficulty, feelings of isolation at work, and unmet expectations are among the top reasons why women leave their careers in science. The COVID-19 pandemic has further contributed to these difficulties as more women are taking additional caregiver roles at home, which in turn impacts their continued employment and career advancement.

To forge a more gender-equal global science community, we need to promote women’s integration in the research environment and workplace by learning about women’s experiences and providing direct support for women in difficulty. Our institutions and organizations should also implement and monitor measures to ensure womens’ career development in a post-pandemic world.

Rashmi Gangadharaiah

Rashmi is a senior research scientist within the AWS organization. She earned her PhD in information technology, artificial intelligence, and machine learning from Carnegie Mellon University.

Rashmi Gangadharaiah
Rashmi Gangadharaiah

As a woman and a mother of two girls, I’m glad that gender equality has been receiving more attention. Just talking about gender equality doesn’t mean that we’ve created a gender-equal community. Here are three steps that we can take to create a gender-equal global science community.

  1. Create opportunities that encourage more women to tackle challenging projects.
  2. Recognize women who have an impact on projects and give credit where it’s due.
  3. We as women should not be afraid to take on challenging projects, grab opportunities that come our way and have a community/support system when the deck is stacked against us.

Antia Lamas-Linares

Antia is a principal research scientist within the AWS Center for Quantum Computing. She earned her PhD in physics from the University of Oxford.

Antia Lamas-linares
Antia Lamas-Linares

Helping diversify science is often not about actions within science, but immediately around science; removing the “death by a thousand cuts” problems.

The most impactful action we can take to improve science careers for women is to prioritize affordable childcare in research campuses (both university and industrial). This also has the very nice feature of benefiting the whole community of researchers, but it would have a disproportionate effect on women, while avoiding the insidious problems of preferential treatment.

If we can make space in campuses for exercise and culture, we can make space for daycares. A second thing we could do is prominently feature female scientists without remarking on their gender, they should not be an anomaly that needs to be highlighted and this narrative can be gently pushed from within organizations. Thirdly, and this is more of a personal action, actively avoid discouraging girls for pursuing geeky interests. Boys get rewarded with questions and attention for this behavior. Girls get the opposite signals.

Bilan Liu

Bilan is an applied robotics scientist within the company’s Lab126 organization. She earned her PhD in electrical and computer engineering at the University of Rochester.

Bilan Liu
Bilan Liu

  • The key aspect for a gender equal world is an environment where women share the same opportunities as men, such as quality education.
  • A gender equal world not only calls for the equality of women, but also quality among women. It is beneficial to share the recognition of successful women, as well as to have supportive peers and mentors for young women.
  • We should advocate to elevate women’s voices, both in the workplace and the media. Increasing the representation of women in a workplace not only creates a better workplace, it also changes perceptions about the value that women bring to the table.

Catherine Benoit Norris

Catherine is a science researcher within the company’s Sustainability organization.  She earned her PhD in business administration from the Université du Québec à Montréal.

Catherine Benoit Norris
Catherine Benoit Norris

  • Acknowledge and support workers, students, professionals, and scientists as parents. Until we fully recognize the needs of families, and have a work culture that allows setting limits, women will continue to be held back.
  • Make sure that everyone speaks and are listened to in meetings. Making sure that everybody is being heard and are being paid attention to when they speak is fundamental for a gender-equal global science community.
  • Support, encourage, value, and recognize women academic achievements. Publicly valuing, rewarding, and celebrating competence and achievements in women is a stepping stone towards gender equality in science and beyond.

Tara Taghavi

Tara is a senior applied scientist within the Alexa AI organization. She earned her PhD in computer science from the University of California, Los Angeles.

Tara Taghavi
Tara Taghavi

A first step in promoting gender equality is to involve more women in hiring processes, particularly hiring loops for science roles.

A second step is to facilitate a more favorable work environment for mothers by providing alternate hours, a reduced time schedule, and similar measures so women can grow their careers as they grow their families.

A third step is to empower women to take management roles. Many statistics have been shared regarding the disproportionate number of women who are promoted in comparison to their male counterparts. We should address it by encouraging women to pursue these roles, and then supporting them as they take on the responsibilities of these higher-level roles.

Nedelina Teneva

Nedelina is an applied scientist (search) within the Alexa organization. She earned her PhD in computer science from the University of Chicago.

Nedelina Teneva
Nedelina Teneva

Engaging in cross-disciplinary collaborations forces us to be curious, empowers us to say “I don’t know” and ask others “What do you think?”. 

This helps us better understand others’ lived experiences. In both professional and personal collaborations, we need to apply more rigorously the scientific method, which minimizes the influence of prejudice, by recognizing our biases or pre-existing beliefs and designing appropriate management strategies.

Finally, we need to continue to solidify these processes into platforms and organizations that nurture diverse opinions. Lessons learned from the existing diversity/inclusion efforts within the science community should be utilized in the broader society. 

Nikhita Vedula

Nikhita is an applied scientist with the Alexa Shopping organization. She earned her PhD in computer science and engineering from Ohio State University.

Nikita Vedula
Nikhita Vedula

Education, encouragement, and awareness are key to fostering the growth of a more gender-equal science community.  Throughout my studies — straight through the completion of my PhD — I have seen at best an 80-20 ratio of men to women in classrooms, and academic or industrial positions. This needs to change, and this change needs to begin within our homes.    

Women require support from both men and other women alike, right from their childhood. We need to inspire and motivate women to nurture their dreams, and pursue their unique passions, instead of telling them things like “This field is for men, not for you”.

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AI Engineer - RL Manipulation, RIVR
CH, Zurich
Are you passionate about pushing the boundaries of what robots can do? Amazon is looking for a creative and driven Applied Scientist to help build intelligent robotic manipulation systems powered by reinforcement learning. In this role, you will research, design, and deploy machine learning solutions that enable robots to interact with the physical world in increasingly capable ways. You will tackle complex, ambiguous problems where textbook answers don't exist, working backwards from real-world needs to invent new approaches. Your work will directly influence how automation systems learn, adapt, and perform at Amazon's scale — and you will see your research come to life on real hardware. Key job responsibilities - Research and develop reinforcement learning methods for robotic manipulation, advancing the state of the art in sim-to-real transfer, contact-rich control, and adaptive grasping strategies. - Design, implement, and evaluate machine learning models and algorithms, leveraging deep learning frameworks such as PyTorch or TensorFlow to train policies that generalize across varied manipulation tasks. - Build and maintain production-quality code that integrates scientific prototypes into larger robotics systems, making thoughtful tradeoffs between complexity, performance, and maintainability. - Collaborate with cross-functional engineering and science teams to define simulation requirements, validate model performance, and iterate on solutions informed by real-world hardware feedback. - Contribute to the team's scientific roadmap by identifying new research directions, mentoring fellow scientists, and publishing results at peer-reviewed venues when appropriate. A day in the life You might start your morning reviewing overnight training runs, analyzing reward curves and failure modes from your latest reinforcement learning experiments. After a quick sync with robotics engineers, you shift to refining a simulation environment to close a gap you spotted between sim and real performance. In the afternoon, you pair with a teammate to design a new evaluation framework, then wrap up by drafting a short write-up of your findings to share with the broader team. About the team Our team sits at the intersection of machine learning research and real-world robotics, focused on teaching robots to manipulate objects with precision and adaptability. We combine reinforcement learning, physics-based simulation, and hands-on hardware validation to deliver solutions that work beyond the lab. We value intellectual curiosity, collaborative problem-solving, and a shared commitment to turning ambitious research ideas into tangible impact. If you are excited about building intelligent systems that learn from experience and operate at scale, this is the team for you.
Economist, Entertainment Economics
US, WA, Seattle
The charter of the Entertainment Economics team includes working on high-impact projects that require economics expertise and a cross-business perspective. Our team supports Amazon’s diverse entertainment businesses – especially Prime Video, Amazon Music, Amazon MGM Studios, and Gaming (Luna) – through complex causal measurements (observational and experimental) and structural modeling. Some of our team’s areas of science expertise include marketing science, long-term value measurement, and experimentation. As a central economics team not embedded in any particular business, we strive to provide objective analyses that take a customer-obsessed, pan-Amazon perspective. This role partners with the Prime Science team to evaluate and improve the way Amazon allocates Prime subscription revenue across its benefit teams, including entertainment businesses. Prime is Amazon's premiere membership program, with over 200mm members world-wide, bringing in billions in Prime subscription revenue annually. Prime is at the center of many major company decisions that impact Amazon's customers. These decisions span a variety of industries, each reflecting the diversity of Prime benefits: fast and free shipping, entertainment & digital content, reading, healthcare, and grocery. Each of these Prime benefits is supported by a different organization, and each relies on Prime subscription revenue to make critical investment decisions. Our team partners with Prime Science to ensure that these allocations are credible, actionable, and incentive compatible for every benefit. To support this work, this role will create science models, validate them, and productionize them. In addition to stellar economics expertise, this role requires systems thinking (anticipating how complex interconnected models will respond to changes in data or modeling), strategic thinking (supporting decisions that affect 200 million+ customers and set Amazon’s direction for years to come), and scientifically novel thinking (using AI and the latest science advancements to achieve move). The ideal candidate is expert in causal inference with experience working in large, complex structural modeling environments. They are a creative problem-solver, able to identify new approaches that solve multiple problems at once while minimizing churn. They think big, not limiting themselves to what’s been done before, while tactfully accounting for the costs of major changes. They can add structure to incredibly ambiguous business contexts, making defensible assumptions and delivering measurements that drive impactful business decisions. They have effective communication and the skill to translate data-driven findings into actionable insights for senior leaders. Finally, they are empathetic and constructive. Our healthy team culture is supportive and fast-paced, and we prioritize learning, growth, and helping each other to continuously raise the bar. Impact and Career Growth In today’s entertainment landscape, critical decisions are made with data and economic models. You’ll help leaders ask the right questions, and then deliver data-driven answers, helping to create the future of Amazon. You’ll help define a long-term science vision in this space and translate it into an actionable roadmap. This role combines science leadership, organizational ability, technical strength, product focus, and business understanding – a perfect recipe for career growth as an economist in tech. Key job responsibilities • Design and build econometric models, especially causal models, to measure the value of the business and its many features • Develop science products from concept to prototype to production, incorporating feedback from scientists and business partners • Independently identify and pursue new opportunities to leverage economic insights across entertainment and Prime • Write business and technical documents communicating business context, methods, and results to business leadership and other scientists • Serve as a technical reviewer for our team and related teams, including document and code reviews
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