Data scientists and data science managers, how many people are on your team? How often do you directly collaborate with your teammates, and what sorts of projects do you tend to collaborate on?
-
-
Replying to @imightbemary
From previous roles, varied between 5-20 although we served very large orgs. My role was strategic and constantly looking for opportunities for the data scientists to show their magic. Projects cover multiple departments, daily collaboration critical to avoid duplication
1 reply 0 retweets 2 likes -
Replying to @Teren_Teh
20! I can't even imagine that. What was your main strategy for avoiding duplication of work?
1 reply 0 retweets 0 likes -
Replying to @imightbemary
More of an art than science but just making sure our team is well connected. There’s one person that generally receives all requests and we discuss before work gets started. Stakeholders are way too eager to ask for help whenever they can.
1 reply 0 retweets 0 likes -
Replying to @Teren_Teh
The eager stakeholder is both a blessing and curse
Does the request-receiver have some sort of official title, sort of like a data science scrum master?1 reply 0 retweets 0 likes -
Replying to @imightbemary
Yes a double edge sword for sure to confuse us all! Unfortunately not official title but that’s a decent idea! Currently, they’re known as the data science product manager. We tend to rotate responsibility to take people out of the firing line. What’s your environment like?
1 reply 0 retweets 0 likes -
Replying to @Teren_Teh
We've taken the approach of embedding DS into specific product groups, and then having DS managers oversee the DS in related product areas. Most work is routed through regular sprint planning, but for unplanned ad hocs, we've got an "on call" rotation to answer small questions
1 reply 0 retweets 1 like -
Replying to @imightbemary
Can the DS rotate if there isn’t enough demand from one group?
1 reply 0 retweets 0 likes
We have yet to encounter that! People do occasionally pitch in on projects where there's domain overlap, though
Loading seems to be taking a while.
Twitter may be over capacity or experiencing a momentary hiccup. Try again or visit Twitter Status for more information.

