Tips for Building a Data Science Capability

across the talent life cycle, including identifying,
acquiring, developing, motivating, and retaining
talent. The model is designed to be comprehensive
to provide the insight and tools needed to help
organizations strategically manage talent and flexible
in allowing an organization to select and focus on
immediate talent needs, where appropriate. In short,
the model is designed to be customized depending
on current organizational talent realities.
The Booz Allen data science Talent Management
Model is not just a grab-and-go “toolkit.” Rather, it’s
a set of comprehensive service offerings that allow
clients to answer three key data science talent
questions: Who do you need? Where do you need
them? How do you keep and develop them? When
Booz Allen created the Talent Management Model,
we intentionally developed service offerings to help
clients who are struggling to answer one or more
of these key questions. Some of the foundational
service offerings, such as the competency
framework and position descriptions, are designed
to be easily customized to an organization’s needs.
Other offerings, such as workforce modeling, needs
assessments, and team building, entail greater
engagement and partnership with clients. Depending
on where an organization falls within the data
science talent spectrum, the Talent Management
Model will help inform which offerings are
most valuable for addressing its data science
talent challenges.
Implementing a Talent Management Model not
only helps data scientists understand their role
and career path within the organization; it helps
organizations establish, manage, and retain
their data science workforce in a strategic and
comprehensive manner.
TALENT MANAGEMENT AS AN ENABLER
FOR SUCCESS
Recruiting and selecting the right talent is a critical
component to building a robust data science workforce
within an organization but it is only a piece
of the talent strategy. To enable data scientists to
flourish and deliver on their promise to enhance
organizational performance, organizations must
consider the full Talent Management Model,
including the amount and type of work to be
performed, the competencies and skills needed
to perform the work, and the development and
retention strategies the organization can employ
to support this kind of unique workforce. By implementing
a comprehensive Talent Management
Model that addresses these critical components,
organizations can achieve an engaged and
successfully performing workforce, while gaining
maximum returns on their analytical investment.
Everything You Need to Know About Managing Your Data Science Talent | 35