Applied Data Science Invited Panel:
“Who is a Data Scientist? Defining the Analytics Profession and Cutting Out the Hype and Confusion”
Wednesday, August 22, 2018 – 1:30-3:30PM – London
Panel Chair: Usama Fayyad, OODA Health and Open Insights, USA
Who gets to call themselves a Data Scientists? An Analytics Professional? This Panel will explore the problems and possibilities in understanding and defining standards on definitions of analytics roles, skill-sets and career paths in the data science industry. As the role of data and analytics is expanding very rapidly in creating new business models or changing existing ones, demand for analytics professionals is growing at an increasing rate. The world has witnessed an explosion in the number of people describing themselves as Data Scientists or Analytics Professionals. Yet in the majority of cases, such people do not fit the bill for an available role. This leaves employers, trainers, educational institutions, recruiters, and customers in a total state of confusion.
Almost every company in the industry has a unique way of defining roles and assigning titles in data analytics related positions. For any given role or title, such as ‘Data Scientist’ or ‘Data Mining Manager’, a variety of role definitions, expected hard and soft skills, expected level of experience, level in the organization, or career development plan including training can be seen. This creates inefficiencies and makes it difficult for companies to find the right match for a given position, leverage analytics skills effectively and retain talent. It also makes it hard for professionals to understand what a certain position requires and develop their own development plans. This has resulted in a chaotic market that is confusing to employers, academic and training institutions, recruiters, managers, customers, and candidates; with a large number of unqualified candidates calling themselves “data scientist” or “analytics professional”.
This panel discussion aims to shed some insight about the analytics profession in practice and the kind of problems faced by organizations in attracting and retaining the right analytics talent. We will discuss topics like the development of standards regarding analytics role definitions, required skills and career advancement paths. This will help set some industry standards which in turn could support the healthy growth of the analytics market. Questions addressed include:
· The true cost of confusion around qualifications for the field, the profession, and organizations attempting to conduct data science
· How do you wade your way through the plethora of individuals claiming they are “Data Scientists”?
· Approaches to effectively identify and retain the true talent
· The need for training and standardization
· Is it about technology tools or is ot about trained qualified people? What are the tradeoffs?
The panelists represent a wide representation of large employers of analytics professions, large enterprises with serious need for data science and analytics, and stakeholders who are trying to address the gaps and define the requirements and qualifications for the relevant roles.