When a US-based healthcare company decided to implement digital technologies to optimise internal processes and develop artificial intelligence (AI) solutions to help customers access services more efficiently, it was faced with a significant challenge: it simply did not have enough employees with the necessary data science skills to achieve these goals.
However, rather than hiring externally, the healthcare company decided it would find a way to upskill and reskill its existing employees. To do this, it joined forces with a range of partners including Microsoft and global education provider General Assembly and launched a pilot data scientist training course.
According to Ryan Fennerty, head of business development and partnerships at General Assembly, the course has been created to help the healthcare company to quickly build “citizen data scientists” who can work across all critical areas of the business.
“Many organisations are prioritising building data-driven mindsets, behaviours and cultures to enable them to innovate more quickly and adopt artificial intelligence (AI) technologies,” he says. “However, a common challenge for many large companies is that their data science skillset is often concentrated in central analytics functions where staff must prioritise mission-critical data projects over everything else. Consequently, most of the other parts of the business are relatively starved of people with the talent and skills needed to fully harness the value of data and inform decision-making in real time.”
Led by practitioner-instructors over a 10-week period in a virtual classroom environment, General Assembly’s Data Scientist course is a project-based, intensive training programme designed to teach advanced data science techniques to data practitioners, such as analytics professionals working in core functions like sales and marketing, business operations, finance and planning, and product management. The 60-hour curriculum is primarily focused on Microsoft tools and technologies.
“The course leverages a range of powerful tools – including Microsoft Power BI, Azure Machine Learning, SQL and open-source libraries in Python – to replicate the workflow of modern data science,” says Fennerty. “Participants learn best practices for data wrangling, data modelling, visualisation and machine learning through a combination of live instruction, sandbox project work and capstone projects. Most of the capstone projects focus on helping participants to use their new data science skills to solve real business problems – for example one project identified an operational efficiency that has the potential to save the company up to $9 million.”
Once they have graduated, participants are better equipped to carry out a range of different tasks and job roles.
“The course is designed to help data practitioners or aspiring data professionals to rapidly build a job-ready set of skills in data analysis, visualisation and predictive modelling for a variety of business needs,” says Fennerty. “Consequently, it is beneficial for individuals who already have experience of working with data and want to break into a dedicated business analytics function within their organisation, or for current data practitioners who want to retool and develop a more advanced skillset appropriate for progressing on a data science career path.”
More than 50 individuals participated in the pilot programmes and, after promising results, the healthcare company plans to extend it to additional teams and business functions as part of a strategic investment in upskilling existing talent in 2021. Meanwhile, Microsoft and General Assembly will expand the programme to additional clients in the USA, Canada, UK and Australia next year too.
“The business benefits of reskilling or upskilling existing employees with the help of partners like General Assembly are clear – data-driven companies that invest deeply in building data science capabilities are able to out-innovate and out-compete their competitors,” says Fennerty.
“Correlation One’s Future of Data Talent report found that 40 per cent of companies were unable to hire or retain data talent due to a lack of supply in 2019, despite the fact that demand for data talent was expected to increase by 20 per cent over the next 12 months. In addition, data science is a field where industry depth is critical because insights can be misleading if employees do not understand the limitations of their organisation’s data sources and are unable to apply sound judgement. As a result, investing in retooling existing employees who know your operations and industry makes sense in a talent-constrained market where competition is fierce.”
Fennerty believes that there are considerable societal benefits to upskilling and reskilling initiatives too.
“We are in the throes of a great employment crisis and many individuals are being forced to rethink their trajectories as the Covid-19 pandemic disrupts vulnerable industries and companies accelerate plans to digitise and automate jobs and functions,” he explains. “Against that backdrop, the projected demand for data roles is enormous, with Microsoft predicting that the number of data analysis, machine learning and AI roles will exceed 20.4 million by 2025, up from 4.6 million today. Together, we have an enormous opportunity to upskill and reskill our communities for the great opportunities of our data- and AI-driven future.”
This article was originally published in the Winter 2020 issue of The Record. To get future issues delivered directly to your inbox, sign up for a free subscription.
Share this story