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Do good: strategies for leading an inclusive data science or statistics consulting team
Published
Author(s)
Christina Maimone, Julia Sharp, Ofira Schwartz-Soicher, Jeffrey Oliver, Lencia Beltran
Abstract
Leading a data science or statistical consulting team in an academic environment can have many challenges including institutional infrastructure, funding, and technical expertise. Even in the most challenging environment, however, leading such a team with inclusive practices can be rewarding for the leader, the team members, and collaborators. We describe nine leadership and management practices that are especially relevant to the dynamics of data science or statistics consulting teams and an academic environment: ensuring people get credit, making tacit knowledge explicit, establishing clear performance review processes, championing career development, empower team members to work autonomously , learning from diverse experiences, supporting team members in navigating power dynamics, having difficult conversations, and developing foundational management skills. Active engagement in these areas will help those who lead data science or statistics consulting groups – whether faculty or staff, regardless of title – create and support inclusive teams.
Maimone, C.
, Sharp, J.
, Schwartz-Soicher, O.
, Oliver, J.
and Beltran, L.
(2024),
Do good: strategies for leading an inclusive data science or statistics consulting team, Stat, [online], https://doi.org/10.1002/sta4.687, https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=957320
(Accessed October 7, 2024)