How Andreia Pierce utilizes her science background in her AWS business role

Being able to understand and relate to the needs of working scientists is key to her success.

As far back as she can remember, Andreia Pierce was fascinated by the human brain. “When I was a kid, I always used to say I wanted to be a neurosurgeon. I grew up in Brazil, and I grew up in a family where everyone is a doctor of sorts, whether it's a PhD, or an MD. So I knew I was going to be one. The MBA came later as my interests evolved.” At 17, she moved to Dallas, Texas, where she knew nobody, and spoke just “a few words” of English. 

Andreia Pierce, seen here sitting while smiling, is the head of business development and strategy in the research vertical for Amazon Web Services.
Andreia Pierce is the head of business development and strategy in the research vertical for Amazon Web Services. She has also worked as a professor, with her own lab, and as a medical science liaison and field director in the pharmaceuticals industry.
Courtesy of Andreia Pierce

Today, Pierce is the head of business development and strategy in the research vertical for Amazon Web Services, which might surprise her younger self. But by pursuing her original dream, and marrying it with self-understanding and plenty of real-world experience, she landed in her current role at the end of 2020. How she arrived there is a lesson in following your deeply held interests throughout your career journey.  

Since Pierce “always tried to do everything as quickly as I can” she finished her undergraduate degree at the University of North Texas in three years and pursued a career in clinical psychology, still thinking about how she could best get into brain research. 

She was working on her PhD studies when she discovered she missed the less clinical, more lab-based work of science. “I realized that I really wanted to be more in touch with the science and the biology. So I stopped that work and took some time away,” she says. 

Her “time away” wasn’t just a vacation.

She took a long break, leaving the US: “I went off to Israel and spent about nine months at a Jewish school for girls, learning Jewish philosophy and Jewish law,” she says. The sabbatical worked. “I figured out what I was going to do to get back on track doing the things that I loved. I joined the PhD program in biomedical sciences [at the University of North Texas Health Science Center] with a focus on neuroscience and pharmacology,” she says. There she got back into lab work, researching the structure and function of the 5-HT3A serotonin receptor. A postdoc at UT Southwestern Medical got her into doing more “initial discovery, and basic research” when she worked at a biophysics lab investigating the membrane bilayer.

From there she assumed she would go on to become a professor with her own lab, feeling “resigned” to that path. “I thought my career was all mapped out. And then I joined the Postdoc Association at UT Southwestern Medical as a member of the board. And somebody suggested that I lead the career development chapter of the association.” In helping other scientists figure out what they should do next, Pierce discovered a new path for herself. “That's when I realized that there were so many other things I could do with a PhD in basic sciences,” she says. 

She’d always loved lab work because of her passion for discovery, but it’s a long process, and the relevance of the work can take decades to come to light. “A few years down the road, it may be relevant to a therapeutic area of expertise somewhere and it may be something that is useful in drug development — or it may not,” Pierce says.

I like speed. I have been described by my husband as somebody who thrives on chaos. So I realized, ‘You know, I can actually be a scientist, a PhD, and a business person.'
Andreia Pierce

She realized she liked a faster-paced environment, closer to the end stage of discovery. “I like speed. I have been described by my husband as somebody who thrives on chaos. So I realized, ‘You know, I can actually be a scientist, a PhD, and a business person. There are other careers outside of academic research that would be very fast paced, where the impact to patients is much more immediate,’” she says. 

That's when Pierce decided to join the pharmaceutical industry. She realized the job of medical science liaison — a fast-paced job where Pierce noted the benefits to patients are more immediate — would allow her to leverage her scientific expertise. She took that position at King Pharmaceuticals, a small company that has since been acquired by Pfizer, followed by UCB, a multinational biopharmaceutical company. “I wasn't just talking about science, but I was talking about science with this added pressure of needing to deliver business results. So I loved it,” she says. 

She joined Teva Pharmaceuticals in 2014, eventually moving up the ranks to field director, where she was awarded a Manager of the Year award. In 2018 she moved to AstraZeneca leading the US field medical team, where she was named an outstanding manager. She was then given the opportunity to move into a global role still at AstraZeneca, developing medical strategy— for 67 different markets and multiple disease states — which enabled her to constantly challenge herself.

“It's interesting how I've specialized over the years in immunology and neurology, and neuro immunology. But I've also leveraged my knowledge of immunology to work in disease states like respiratory disorders, which is not neurology at all. It's that ability to flex, and the desire to always learn new things that was so great about that work. I like change. And switching to the business side allowed me to leverage science in a way that every two, three years, I'm having to learn something completely different,” she says.

Switching to the business side allowed me to leverage science in a way that every two, three years, I'm having to learn something completely different.
Andreia Pierce

As her career progressed, Pierce became more and more interested in the business strategy side, which she says “increasingly drives and interests me.” She used whatever time she could find in the evenings and weekends to acquire an MBA from the Southeastern Oklahoma State University, deepening her commitment to a business career. When she decided to open her LinkedIn profile to recruiters in 2019, Amazon reached out. Pierce was surprised.

“I remember looking at the email and going ‘Amazon, what am I going to do at Amazon?’” Then she took a closer look and discovered the company was interested in her leading a team of research subject matter experts on the business side of AWS. That’s when she realized, “Wow! This role was made for me,” she says. 

She loved that the job would give her the opportunity to be a business leader who draws on scientific insight. It gave her the opportunity to not only transition to a business-centric role, but to do it in a way that leveraged her science knowledge. “I didn’t feel like I was neglecting, giving up, or not using all those years that I had spent becoming good at science,” she says. And that experience — being able to understand and relate to the needs of working scientists — is key to her work today. 

Now she leads a team of PhDs who support account managers in the field, the enterprise sales team, as well as people who work internally repackaging AWS cloud computing solutions, creating sales plays and go-to-market plans, to meet the needs of researchers. 

“What my team does is really try to work all angles around helping researchers and academic institutions, federal agencies, and nonprofits to migrate their workloads to the cloud, with the objective of making things faster, easier, and more accurate so they can accelerate the timeline from raw data to results,” she says.

That includes working with a large variety of organizations including biomedical, digital agriculture, veterinary medicine, and on the non-medical side, digital humanities, engineering, applied physics, and even law. Those include University of California, Davis and New York University as well as national and international research agencies like National Aeronautics and Space Administration (NASA), National Science Foundation (NSF), and National Institutes of Health (NIH).

Think outside the box and ask people, ‘Hey, how'd you get to this role and what is it like’? And really try to understand what it is that you want to accomplish.
Andreia Pierce

For scientists interested in pursuing a business role, Pierce recommends talking to people. She suggests joining networking groups, serving on boards of different associations, and finding creative ways to meet new people. “Think outside the box and ask people, ‘Hey, how'd you get to this role and what is it like’? And really try to understand what it is that you want to accomplish,” she says. 

And, she advises, take those steps, even if you aren’t completely clear on specifics.

“I may not have known the titles I wanted to have. But by the time I switched to pharma I knew I wanted to lead a business. And I wanted to do it in a way that was very impactful, where I could create the strategy and have a seat at the table and implement change, not just change things once they have been rolled out to me, but be part of building it.”

Ultimately, she says her career has benefitted from deciding where she wanted to be and, in true Amazonian fashion, working backwards from there.

Pierce writes about how the Maryland Transportation Institute is tracking social distancing efforts with the AWS Cloud and big data.

Research areas

Related content

US, MA, Boston
The Artificial General Intelligence (AGI) team is looking for a passionate, talented, and inventive Applied Scientist with a strong deep learning background, to build industry-leading technology with Large Language Models (LLMs) and multi-modal systems. You will support projects that work on technologies including multi-modal model alignment, moderation systems and evaluation. Key job responsibilities As an Applied Scientist with the AGI team, you will support the development of novel algorithms and modeling techniques, to advance the state of the art with LLMs. Your work will directly impact our customers in the form of products and services that make use of speech and language technology. You will leverage Amazon’s heterogeneous data sources and large-scale computing resources to accelerate advances in generative artificial intelligence (GenAI). You are also expected to publish in top tier conferences. About the team The AGI team has a mission to push the envelope in LLMs and multimodal systems. Specifically, we focus on model alignment with an aim to maintain safety while not denting utility, in order to provide the best-possible experience for our customers.
US, WA, Seattle
Do you want to re-invent how millions of people consume video content on their TVs, Tablets and Alexa? We are building a free to watch streaming service called Fire TV Channels (https://techcrunch.com/2023/08/21/amazon-launches-fire-tv-channels-app-400-fast-channels/). Our goal is to provide customers with a delightful and personalized experience for consuming content across News, Sports, Cooking, Gaming, Entertainment, Lifestyle and more. You will work closely with engineering and product stakeholders to realize our ambitious product vision. You will get to work with Generative AI and other state of the art technologies to help build personalization and recommendation solutions from the ground up. You will be in the driver's seat to present customers with content they will love. Using Amazon’s large-scale computing resources, you will ask research questions about customer behavior, build state-of-the-art models to generate recommendations and run these models to enhance the customer experience. You will participate in the Amazon ML community and mentor Applied Scientists and Software Engineers with a strong interest in and knowledge of ML. Your work will directly benefit customers and you will measure the impact using scientific tools.
IN, HR, Gurugram
Our customers have immense faith in our ability to deliver packages timely and as expected. A well planned network seamlessly scales to handle millions of package movements a day. It has monitoring mechanisms that detect failures before they even happen (such as predicting network congestion, operations breakdown), and perform proactive corrective actions. When failures do happen, it has inbuilt redundancies to mitigate impact (such as determine other routes or service providers that can handle the extra load), and avoids relying on single points of failure (service provider, node, or arc). Finally, it is cost optimal, so that customers can be passed the benefit from an efficiently set up network. Amazon Shipping is hiring Applied Scientists to help improve our ability to plan and execute package movements. As an Applied Scientist in Amazon Shipping, you will work on multiple challenging machine learning problems spread across a wide spectrum of business problems. You will build ML models to help our transportation cost auditing platforms effectively audit off-manifest (discrepancies between planned and actual shipping cost). You will build models to improve the quality of financial and planning data by accurately predicting ship cost at a package level. Your models will help forecast the packages required to be pick from shipper warehouses to reduce First Mile shipping cost. Using signals from within the transportation network (such as network load, and velocity of movements derived from package scan events) and outside (such as weather signals), you will build models that predict delivery delay for every package. These models will help improve buyer experience by triggering early corrective actions, and generating proactive customer notifications. Your role will require you to demonstrate Think Big and Invent and Simplify, by refining and translating Transportation domain-related business problems into one or more Machine Learning problems. You will use techniques from a wide array of machine learning paradigms, such as supervised, unsupervised, semi-supervised and reinforcement learning. Your model choices will include, but not be limited to, linear/logistic models, tree based models, deep learning models, ensemble models, and Q-learning models. You will use techniques such as LIME and SHAP to make your models interpretable for your customers. You will employ a family of reusable modelling solutions to ensure that your ML solution scales across multiple regions (such as North America, Europe, Asia) and package movement types (such as small parcel movements and truck movements). You will partner with Applied Scientists and Research Scientists from other teams in US and India working on related business domains. Your models are expected to be of production quality, and will be directly used in production services. You will work as part of a diverse data science and engineering team comprising of other Applied Scientists, Software Development Engineers and Business Intelligence Engineers. You will participate in the Amazon ML community by authoring scientific papers and submitting them to Machine Learning conferences. You will mentor Applied Scientists and Software Development Engineers having a strong interest in ML. You will also be called upon to provide ML consultation outside your team for other problem statements. If you are excited by this charter, come join us!
US, MA, Boston
The Artificial General Intelligence (AGI) team is looking for a passionate, talented, and inventive Senior Applied Scientist with a strong deep learning background, to build industry-leading technology with Large Language Models (LLMs) and multimodal systems. Key job responsibilities As a Senior Applied Scientist with the AGI team, you will work with talented peers to lead the development of novel algorithms and modeling techniques, to advance the state of the art with LLMs. Your work will directly impact our customers in the form of products and services that make use of speech and language technology. You will leverage Amazon’s heterogeneous data sources and large-scale computing resources to accelerate advances in generative artificial intelligence (GenAI). About the team The AGI team has a mission to push the envelope in LLMs and multimodal systems, in order to provide the best-possible experience for our customers.
IN, KA, Bengaluru
The Amazon Alexa AI team in India is seeking a talented, self-driven Applied Scientist to work on prototyping, optimizing, and deploying ML algorithms within the realm of Generative AI. Key responsibilities include: - Research, experiment and build Proof Of Concepts advancing the state of the art in AI & ML for GenAI. - Collaborate with cross-functional teams to architect and execute technically rigorous AI projects. - Thrive in dynamic environments, adapting quickly to evolving technical requirements and deadlines. - Engage in effective technical communication (written & spoken) with coordination across teams. - Conduct thorough documentation of algorithms, methodologies, and findings for transparency and reproducibility. - Publish research papers in internal and external venues of repute - Support on-call activities for critical issues Basic Qualifications: - Master’s or PhD in computer science, statistics or a related field - 2-7 years experience in deep learning, machine learning, and data science. - Proficiency in coding and software development, with a strong focus on machine learning frameworks. - Experience in Python, or another language; command line usage; familiarity with Linux and AWS ecosystems. - Understanding of relevant statistical measures such as confidence intervals, significance of error measurements, development and evaluation data sets, etc. - Excellent communication skills (written & spoken) and ability to collaborate effectively in a distributed, cross-functional team setting. - Papers published in AI/ML venues of repute Preferred Qualifications: - Track record of diving into data to discover hidden patterns and conducting error/deviation analysis - Ability to develop experimental and analytic plans for data modeling processes, use of strong baselines, ability to accurately determine cause and effect relations - The motivation to achieve results in a fast-paced environment. - Exceptional level of organization and strong attention to detail - Comfortable working in a fast paced, highly collaborative, dynamic work environment
IN, KA, Bengaluru
Amazon 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. The ATT team, based in Bangalore, is responsible for ensuring that ads are relevant and is of good quality, leading to higher conversion for the sellers and providing a great experience for the customers. We deal with one of the world’s largest product catalog, handle billions of requests a day with plans to grow it by order of magnitude and use automated systems to validate tens of millions of offers submitted by thousands of merchants in multiple countries and languages. In this role, you will build and develop ML models to address content understanding problems in Ads. These models will rely on a variety of visual and textual features requiring expertise in both domains. These models need to scale to multiple languages and countries. You will collaborate with engineers and other scientists to build, train and deploy these models. As part of these activities, you will develop production level code that enables moderation of millions of ads submitted each day.
US, WA, Seattle
The Search Supply & Experiences team, within Sponsored Products, is seeking an Applied Scientist to solve challenging problems in natural language understanding, personalization, and other areas using the latest techniques in machine learning. In our team, you will have the opportunity to create new ads experiences that elevate the shopping experience for our hundreds of millions customers worldwide. As an Applied Scientist, you will partner with other talented scientists and engineers to design, train, test, and deploy machine learning models. You will be responsible for translating business and engineering requirements into deliverables, and performing detailed experiment analysis to determine how shoppers and advertisers are responding to your changes. We are looking for candidates who thrive in an exciting, fast-paced environment and who have a strong personal interest in learning, researching, and creating new technologies with high customer impact. Key job responsibilities As an Applied Scientist on the Search Supply & Experiences team you will: - Perform hands-on analysis and modeling of enormous datasets to develop insights that increase traffic monetization and merchandise sales, without compromising the shopper experience. - Drive end-to-end machine learning projects that have a high degree of ambiguity, scale, and complexity. - Build machine learning models, perform proof-of-concept, experiment, optimize, and deploy your models into production; work closely with software engineers to assist in productionizing your ML models. - Design and run experiments, gather data, and perform statistical analysis. - Establish scalable, efficient, automated processes for large-scale data analysis, machine-learning model development, model validation and serving. - Stay up to date on the latest advances in machine learning. About the team We are a customer-obsessed team of engineers, technologists, product leaders, and scientists. We are focused on continuous exploration of contexts and creatives where advertising delivers value to shoppers and advertisers. We specifically work on new ads experiences globally with the goal of helping shoppers make the most informed purchase decision. We obsess about our customers and we are continuously innovating on their behalf to enrich their shopping experience on Amazon
US, WA, Seattle
Have you ever wondered how Amazon launches and maintains a consistent customer experience across hundreds of countries and languages it serves its customers? Are you passionate about data and mathematics, and hope to impact the experience of millions of customers? Are you obsessed with designing simple algorithmic solutions to very challenging problems? If so, we look forward to hearing from you! At Amazon, we strive to be Earth's most customer-centric company, where both internal and external customers can find and discover anything they want in their own language of preference. Our Translations Services (TS) team plays a pivotal role in expanding the reach of our marketplace worldwide and enables thousands of developers and other stakeholders (Product Managers, Program Managers, Linguists) in developing locale specific solutions. Amazon Translations Services (TS) is seeking an Applied Scientist to be based in our Seattle office. As a key member of the Science and Engineering team of TS, this person will be responsible for designing algorithmic solutions based on data and mathematics for translating billions of words annually across 130+ and expanding set of locales. The successful applicant will ensure that there is minimal human touch involved in any language translation and accurate translated text is available to our worldwide customers in a streamlined and optimized manner. With access to vast amounts of data, cutting-edge technology, and a diverse community of talented individuals, you will have the opportunity to make a meaningful impact on the way customers and stakeholders engage with Amazon and our platform worldwide. Together, we will drive innovation, solve complex problems, and shape the future of e-commerce. Key job responsibilities * Apply your expertise in LLM models to design, develop, and implement scalable machine learning solutions that address complex language translation-related challenges in the eCommerce space. * Collaborate with cross-functional teams, including software engineers, data scientists, and product managers, to define project requirements, establish success metrics, and deliver high-quality solutions. * Conduct thorough data analysis to gain insights, identify patterns, and drive actionable recommendations that enhance seller performance and customer experiences across various international marketplaces. * Continuously explore and evaluate state-of-the-art modeling techniques and methodologies to improve the accuracy and efficiency of language translation-related systems. * Communicate complex technical concepts effectively to both technical and non-technical stakeholders, providing clear explanations and guidance on proposed solutions and their potential impact. About the team We are a start-up mindset team. As the long-term technical strategy is still taking shape, there is a lot of opportunity for this fresh Science team to innovate by leveraging Gen AI technoligies to build scalable solutions from scratch. Our Vision: Language will not stand in the way of anyone on earth using Amazon products and services. Our Mission: We are the enablers and guardians of translation for Amazon's customers. We do this by offering hands-off-the-wheel service to all Amazon teams, optimizing translation quality and speed at the lowest cost possible.
US, WA, Seattle
Amazon.com strives to be Earth's most customer-centric company where customers can shop in our stores to find and discover anything they want to buy. We hire the world's brightest minds, offering them a fast paced, technologically sophisticated and friendly work environment. Economists at Amazon partner closely with senior management, business stakeholders, scientist and engineers, and economist leadership to solve key business problems ranging from Amazon Web Services, Kindle, Prime, inventory planning, international retail, third party merchants, search, pricing, labor and employment planning, effective benefits (health, retirement, etc.) and beyond. Amazon Economists build econometric models using our world class data systems and apply approaches from a variety of skillsets – applied macro/time series, applied micro, econometric theory, empirical IO, empirical health, labor, public economics and related fields are all highly valued skillsets at Amazon. You will work in a fast moving environment to solve business problems as a member of either a cross-functional team embedded within a business unit or a central science and economics organization. You will be expected to develop techniques that apply econometrics to large data sets, address quantitative problems, and contribute to the design of automated systems around the company. About the team The International Seller Services (ISS) Economics team is a dynamic group at the forefront of shaping Amazon's global seller ecosystem. As part of ISS, we drive innovation and growth through sophisticated economic analysis and data-driven insights. Our mission is critical: we're transforming how Amazon empowers millions of international sellers to succeed in the digital marketplace. Our team stands at the intersection of innovative technology and practical business solutions. We're leading Amazon's transformation in seller services through work with Large Language Models (LLMs) and generative AI, while tackling fundamental questions about seller growth, marketplace dynamics, and operational efficiency. What sets us apart is our unique blend of rigorous economic methodology and practical business impact. We're not just analyzing data – we're building the frameworks and measurement systems that will define the future of Amazon's seller services. Whether we're optimizing the seller journey, evaluating new technologies, or designing innovative service models, our team transforms complex economic challenges into actionable insights that drive real-world results. Join us in shaping how millions of businesses worldwide succeed on Amazon's marketplace, while working on problems that combine economic theory, advanced analytics, and innovative technology.
US, WA, Seattle
We’re working on the future. If you are seeking an iterative fast-paced environment where you can drive innovation, apply state-of-the-art technologies to solve large-scale real world delivery challenges, and provide visible benefit to end-users, this is your opportunity. Come work on the Amazon Prime Air Team! We are seeking a highly skilled weather scientist to help invent and develop new models and strategies to support Prime Air’s drone delivery program. In this role, you will develop, build, and implement novel weather solutions using your expertise in atmospheric science, data science, and software development. You will be supported by a team of world class software engineers, systems engineers, and other scientists. Your work will drive cross-functional decision-making through your excellent oral and written communication skills, define system architecture and requirements, enable the scaling of Prime Air’s operation, and produce innovative technological breakthroughs that unlock opportunities to meet our customers' evolving demands. About the team Prime air has ambitious goals to offer its service to an increasing number of customers. Enabling a lot of concurrent flights over many different locations is central to reaching more customers. To this end, the weather team is building algorithms, tools and services for the safe and efficient operation of prime air's autonomous drone fleet.