Bayer Equips Crop Science Division with AWS Skills and Launches Innovative Decision Science Ecosystem

Bayer is a multinational life science company that specializes in healthcare and agriculture markets.  With a history spanning over 150 years, Bayer began in Germany and now operates globally through subsidiaries across Europe, the Americas, Asia-Pacific, Africa, and the Middle East.

The company’s mission is “Health for all, Hunger for none.” Part of Bayer, the Crop Science division is a leader in seed innovation, crop protection, and digital farming, As the global population grows, innovative solutions are needed to produce food, fiber, and fuel, while restoring resources like soil and water and addressing climate change. To meet these demands, farmers must increase crop production by 50 percent by 2050. Bayer is collaborating with farmers and partners to promote and scale regenerative agriculture, enabling a future where farming can produce more while restoring the environment.

Since 2014, Bayer has been powering its mission by developing solutions on AWS. Using AWS's performance and scalability, the division is accelerating its data science and AI capabilities. Today, Bayer is transitioning to its next-generation data science platform, the Decision Science Ecosystem (DSE). This platform, developed through a collaborative effort between Bayer and AWS, integrates AWS technologies, customized to meet Bayer's unique needs. The DSE empowers thousands of Bayer’s data scientists and engineers with a unified platform built on Amazon SageMaker Studio, enhanced with Amazon Bedrock for diagnostic capabilities, and Amazon Q to improve developer productivity while reducing the engineering support burden.

“The DSE is both a technology and a cultural approach to bringing decision science to a centralized environment where individuals can share code and models, streamlining the work to deliver the necessary technologies,” says Randall Morris, decision science adoption lead for the Decision Science Ecosystem at Bayer. “By leveraging the full power of AWS with customizations for Bayer, our teams can quickly re-deploy environments and get models into production efficiently.”

To help data scientists and engineers realize the full potential of the DSE to drive innovation, Bayer needed to upskill them with the latest AWS skillsets to ensure they were ready to work with DSE. Says Morris, “We needed to bridge any gaps between our current AWS skillsets and those needed for the DSE.”

Recognizing that upskilling its employees was crucial to fully leveraging the capabilities of the DSE platform and AWS Services, Bayer focused on enhancing its teams' AWS Cloud fluency. It collaborated with AWS Training and Certification to optimize upskilling and develop persona-based AWS beginner, intermediate, and expert learning pathways for data scientists, engineers, analysts, and managers. Colleen Young, training lead for the Decision Science Ecosystem at Bayer, says, “One of the essential things AWS Training and Certification offered our learners was a relevant and relatable curriculum. Its learning paths delivered skillsets that employees could apply in their daily work.”

As part of the global training program, participants engaged in virtual AWS Classroom Training  and on-demand learning with AWS Skill Builder, an online learning center with more than 600 digital courses and learning plans. Over 1,000 Bayer employees took part in AWS training, with approximately 640 participating in AWS Skill Builder courses. Comments Young, “With AWS Skill Builder, employees could set their own pace of learning, which is beneficial for a corporate schedule. When we did our first AWS Learning Need Analysis, we discovered that employees overwhelmingly preferred that training style.”

Besides AWS Skill Builder, approximately 350 DSE users participated in the instructor-led training to use various technologies such as Amazon SageMaker. 60 users also participated in on-site, hands-on Immersion Days led by AWS instructors. Those new to AWS found the AWS Technical Essentials courses helpful in building confidence with AWS terminology, concepts, and the AWS Management Console. Young adds, “AWS training has given us the skills to migrate from other services and platforms and focus primarily on AWS to increase collaboration.”

Equipped with new AWS skills, Bayer’s data science teams are leveraging the full capabilities of the DSE platform to accelerate innovation, improve decision-making through data insights, and explore new opportunities in sustainable and regenerative agricultural practices.

While the platform continues to be refined, data teams worldwide are already working more effectively and AI building models in Amazon SageMaker. Pedro Veronezi, data analytics platform lead at Bayer, “Standardizing on AWS means we can reuse and share tools and services across data teams, increasing our speed of AI- and ML-based innovation." He adds, “Previously, a non-standardized approach meant that provisioning a cloud environment could take days for a data team within Bayer. Now, we can launch an environment on AWS in just a few hours.”

The DSE's built-in guardrails also allow data science teams to focus on their work rather than handling cybersecurity issues, as Morris explains, “The data science team knows how to use capabilities in Amazon Bedrock to diagnose issues if they arise, reducing their dependence on IT support and accelerating progress.”

The training has also enabled Bayer to use specific services like Amazon Q more effectively. It is using Amazon Q to enhance platform documentation, enabling 70 percent faster onboarding of data science colleagues. Additionally, it is automating tasks with Amazon Q, increasing development productivity by up to 30 percent. As Young reflects, “Before AWS training, only 20 percent of Bayer’s DSE users felt comfortable with AWS technologies. Post-training, over 70 percent of users now feel confident navigating AWS services, allowing them to innovate more efficiently.” This boost in cloud fluency has directly contributed to Bayer’s ability to innovate faster.

As Bayer continues to equip employees with AWS skills, the company is poised to accelerate innovation, improve decision-making through data insights, and explore new opportunities in sustainable and regenerative agricultural practices. The first wave of users started using the DSE platform in October 2024, with teams across all regions expected to gain access within 12 months.

Looking ahead, Veronezi highlights the benefits of upskilling. He says, “Due to AWS training, we'll be able to capture value from our platform from the start. The ability to launch development environments that are safe and secure for data scientists in a matter of hours instead of days changes how we're doing data science, helping us innovate rapidly and deliver insights back to the business—which will ultimately help us create better solutions for our customers.”