Mission is launching a dedicated Data, Analytics, & Machine Learning practice for Amazon Web Services, according to a press release on the company’s website. The new practice provides data engineering, analytics, machine learning, and data science expertise and tools to customers. This branch is led by Dr. Ryan Ries, who has 15 years of experience leading data science and engineering initiatives.

Mission is an AWS managed service provider formed in 2018 when IT solutions and consultancy providers Reliam, Stratalux, and G2 Tech Group merged together. The company provides managed services for AWS deployments, AWS migration planning and implementation, AWS disaster recovery, and AWS consultancy services. Mission also offers cloud spend and performance optimization strategy planning, as well as delivering managed DevOps, managed cloud security, and managed application performance monitoring.

The Data, Analytics, & Machine Learning lets users gain more insight from their data on AWS through custom-built algorithms that unearth data-driven insights. Customers can run data models more efficiently with Mission-designed CI/CD pipelines and identify patterns to unlock business insights. Users will also be able to leverage powerful AWS databases via Mission’s expertise with cloud-native services such as Amazon Redshift.

In the company’s press release, Mission’s VP of Consulting Services Jaret Chiles stated: “Organizations have a huge opportunity to let their data affect change. Regardless of company size, regardless of industry – connecting disparate data sources and deriving insight from that data continues to be a monumental challenge for businesses that don’t have the requisite (and expensive) expertise in-house. We are launching our new practice to move data and analytics modernization from goal to reality – quickly and with processes and technologies built for our customers’ long-term success.”

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From dictating which posts appear in our social media feeds to deciding whether or not a suspect might be guilty of a crime, data and computing have come to permeate nearly all aspects of our lives. But while these systems can offer many benefits, their faults — whether data breaches, unintentional biases in algorithms or the proliferation of misinformation — can have disastrous effects, especially on already marginalized individuals and communities.

That’s why Jennifer Chayes, UC Berkeley’s new data science leader, is dedicated to creating an environment where data and computing are informed by leaders from all disciplines, including ethics and the humanities, and where people of all races, genders and socioeconomic backgrounds are welcomed at the table.

Chayes, associate provost of the Division of Computing, Data Science, and Society (CDSS) and dean of the School of Information at Berkeley, discussed her vision for the future of CDSS at a virtual Campus Conversations event on Wednesday.

 “More and more of our public systems — (our) criminal justice system, our health system, our education system, our social welfare system — [are] being mediated by computing. … As [data science] becomes the fabric of our society, [we need to ensure) that it is a fabric that will serve its purpose properly,” Chayes said. “We need women, we need Black people, we need Latinx and Indigenous people building this fabric, because they will understand in ways different from the majority how [data] may be used.”

Chayes left her position as a technical fellow at Microsoft Research to lead CDSS in January 2020. Part of what drew her to Berkeley was the sheer scale of the data science research happening on campus, coupled with the wide variety of fields data scientists were working in — from climate change and sustainability to biomedicine and public health to human rights.

“I think, at Berkeley, we are going to have just many, many more disciplines interacting with each other,” Chayes said, when asked about her hopes for the future of the division. “I will feel like a failure if we don’t have joint faculty with every division and school and college on campus … because I think that all voices have to be here, everyone has to be at the table for this to be a success.”

To help increase racial diversity in data science fields, Chayes said that the division has approached historically Black colleges and universities about creating joint master’s programs. The data science major also tends to attract a diverse array of students, many of whom didn’t necessarily intend to go into data and computing when they entered Berkeley.

The CDSS is also planning the construction of a new data science building that will include extensive convening space for students, staff and faculty to collaborate.

“People really need to mix with each other,” Chayes said. “It’s something that I learned at Microsoft. I tried to have as flat of organizations as possible with philosophers, anthropologists and biologists and physicists and mathematicians and computer scientists and lawyers coming together and talking with each other. …  It’s not just learning the language of another discipline, … it is really understanding what are the important problems of other disciplines and why.”

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