Instead of using the catchall title of “data scientist,” data professionals — and the people who hire and work with them — would benefit from using more specific job titles based on the four emerging specializations for mid-career data professionals.
We’ve combined our thinking around mid-career data roles with two other simple observations:
- Teams have entry-level roles that require a common baseline of foundational skills.
- Teams have leadership roles that require general management skills.
Guided by these findings, we’ve created a comprehensive career framework that delineates the possible growth paths of an individual working in data science. It defines the path an individual takes from an entry-level stage, though a mid-career specialization, into a leadership role.
Let’s break down each section of the framework.
Level 1: Foundation (Entry-Level)
To begin a career in data science, individuals need the bundle of skills in Level 1: wrangling, exploring, modeling, and communicating. With these abilities, professionals can execute on well-scoped tasks while relying on the guidance of experienced teammates. Level 1 skills serve as common building blocks and foundation for each of the specializations in Level 2, and they’re essential irrespective of company domain and size.
Level 2: Application (Mid-Career)
Experienced data professionals typically specialize in one of the four Level 2 domains, each of which require a different focus, whether it be organizing complex data or predicting relationships among variables. Thus, instead of calling everyone within Level 2 data scientists, we instead call them data engineers, quantitative researchers, machine learning engineers, and advanced data analysts, to reflect the unique nuances of each concentration.
Level 3: Leadership (Senior Role/Management)
For team members who seek leadership roles, Level 3 contains the bundle of additional skills — in business, governance, and people — needed to be a successful data team leader. Because these roles require generalization and problem-solving across the stack, successful Level 3s have often covered more than one Level 2 specialization during their careers.