How the IBM Data Science and AI Elite team trains organizations to tackle data science faster

From patient risk prediction to package delivery, meet the team making global strides with data science

By | 5 minute read | October 27, 2020

Today, the world looks different — from last year, last month, and even yesterday. The ever-changing status of our surroundings brings new problems, and having the right skills becomes critical to adapting and innovating in the face of these challenges.

However, according to The Quant Crunch report, “data science skills are one of the most challenging to recruit for, and can potentially create the greatest disruption if not filled.”

That’s where we come in. Our team thrives on tackling data science problems head-on. The IBM Data Science and AI Elite (DSE) engages with organizations across every industry, offering the right expertise to help teams tackle data science use cases and overcome the challenges of AI adoption.

At the beginning in 2018, Rob Thomas, IBM Senior Vice President Cloud and Data platform, envisioned a team of world-class data scientists to engage with clients and organizations to put data science to work — and the DSE did just that. Over the past three years and counting, the IBM Data Science and AI Elite has completed engagements in 50 countries across 6 industry sectors with the leadership of nearly 100 data scientists. From reducing overall carbon footprint or litter on beaches, to minimizing lost parcels or ensuring your package is properly delivered, the impact our engagements continue to drive for citizens globally is resounding. We’ve helped organizations improve accuracy in finding lost shipments by 20%, process transportation data 423 times faster, reduce telecom operating costs by 15%, proactively mitigate bias in a company’s hiring process and more. Our recent work with Highmark Health, Rolls-Royce with the Emergent Alliance, and United Nations Environment Programme (UNEP) are just a few of the many engagements that use AI to bring change for good.

From 12 months to a few days

With 720,000 cases annually in the U.S., and a staggering mortality rate between 25 and 50%, sepsis isn’t just life-threatening; it doubles as one of the country’s most expensive inpatient conditions, consuming more than $27 billion annually.

Working with the DSE, organizations like Highmark have made tremendous leaps forward using inpatient clinical data to build models to predict — and prevent — sepsis mortality. Typically, this work takes up to 12+ months for Highmark to complete, Curren Katz, Director of Data Science, R&D at Highmark Health, shares in a recent discussion about the project. But the IBM Cloud Pak for Data platform “took care of the heavy lifting behind the scenes and allowed the DSE team to come back with a deployed model within just a few days.”

Cloud Pak for Data shined as a common language platform by enabling explainability in Highmark’s models, and also made way for Highmark to quickly respond to the growing COVID crisis. The newly launched platform gives Katz the power to scoop up new research findings and contributors as COVID-19 evolves, changes and prompts new data.

Moving the needle on economic recovery

In a similar vein, Rolls Royce rallied recovery by bringing together IBM and dozens of global enterprises to create the Emergent Alliance, a non-profit community of technology companies and data science professionals who share the belief that data and AI will help accelerate economic recovery from COVID-19. Recently efforts in teaming with IBM were focused on solving the recent Emergent Alliance challenge statement: how a trusted and explainable risk-pulse index could help businesses emerge stronger after the pandemic.

IBM and Rolls-Royce R²Data Labs innovated to analyze a broad set of economic, behavioral and sentiment data to build economic resilience, find the pulse of an unprecedented crisis and help businesses emerge stronger post-pandemic.

Digging up data to eliminate beach litter

As global citizens, our choices lead to environmental impact — especially in the area of marine litter and beach cleanup efforts. The United Nations Development Programme (UNDP) set a goal of significantly reducing marine pollution by 2025, which called for the creation of an index to measure coastal eutrophication and the density of floating plastic. The DSE joined forces with the United Nations Environment Programme (UNEP) and the Wilson Center to address the shortage of a centralized global marine litter database and access to data across the globe.

With no process in place to deliver data on the amount of plastic polluting beaches today, these stakeholders put their heads together to pilot a global platform for marine litter. IBM Watson Knowledge Catalog on IBM Cloud Pak for Data allowed UNEP and IBM to automatically clean, crosswalk, classify, conform and make the right data available quickly for data scientists. WKC also allows citizen scientists to trace origins of the data, collaborate with other scientists, request datasets and share their insights on the dataset using rating and tagging mechanisms, making a huge leap toward eliminating plastic on beaches for good. Likewise, thanks to IBM Watson Assistant, we met the world’s first virtual environmental advocate — Sam — designed to unify researchers, communities and policymakers, to get all stakeholders on board.

Helping organizations accelerate time to value

These are just a few of the many organizations that joined forces with our team to make great waves with data science. Additionally, we often see patterns arise between use cases, which fuels the opportunity for the team to build industry accelerators based on real client experiences. By packaging up use-case-specific, applicable assets for model deployment, industry accelerators can shorten the time to value on your next data science project significantly. For an extra hand getting started, our Data Science and AI Elite experts are ready to help by bringing diverse backgrounds and a wide array of skills to the table.

Moreover, in light of recent circumstances caused by the global pandemic, our team also crafted a Remote Data Science Toolkit as a gift to our community to help data scientists everywhere do their best work from home.

It is thrilling to reflect back on the accomplishments of our clients and organizations across the globe with the help of the IBM Data Science and AI Elite. Yet, as the market continues to shift, there is always more work to be done. Looking ahead, digital transformation will pave the way for organizations into the next era of AI. I am eager to see how the DSE continues to help clients transform the world around us, adapt to market trends and put data science to work.

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