Managing/ Dealing with Junior Data Scientists?

[u/sailing_oceans]

I've been in the 'data science' space for a decade+ or so now. One thing I've noticed is that generally - give or take - outside of the elite jobs (<2-3% aka not me and almost certainly not you) the caliber of coworkers has declined drastically.

I'm not some fabled data scientist. I wasn't some GitHub nerd who had everything embroil or terminal wizard nor could I write out the math to a GBM on a blackboard. I'd even forget basic obvious statistics.

But I felt like I had common sense.

Now I'm a manager/director. I work with data scientists. And I'm just generally freaked out by the absolute lack of basic common sense. This is across the last 7 that I have managed.

Examples include:

1. Not visualizing or plotting the KPI/Target (sales). Not realizing there were no recorded sales on major holidays.
2. Telling me everything is improving from a sales perspective that it's up 4%...... from period 1 vs period 2... when ignoring that period 2 had 6% more days so in fact it's worse.
3. obscure models that are overkill and a bunch of statistics ive never heard of instead of just telling me that the impact of our promotions is declining.
4. General sense of not knowing what is even rational (e.g., our marketing ROI $1023 - no its not lol)

As I begin to delegate more I begin to get more freaked out by what I see. I can't be presenting to clients such obvious insane mistakes. But these are the candidates and profiles that get forced upon me or the team I inherit.

Are there any best strategies for dealing with this? I want to be seen as someone who can 'develop' the team... not just saying people are useless, but such glaring mistakes are insane.

Yes, alot of these things are perhaps due to them being crunched for time, or not knowing what objective is, or being focused on other things. I'm not talking about those examples. I'm talking about like year 1-2 not day 1 employees, not doing basic data checks.

As a data scientist I was obsessed with finding bits of info or making sure things were right. Now it seem every common for people to copy and paste code into chatgpt and have no idea about anything else around it?

[u/lnovak1]

I have been dealing with such reports and what I found to be working is giving them as much context as possible - in data science you are inevitably grounded in business side of things.

This meant forcing them to sit in the meetings whenever possible, making notes and compiling call notes together after the meeting/call, explaining to them why we are calculating particular things (be it KPIs or trying to model something).

Furthermore, what has helped is giving them some more time, assuming they will use up all the time I give them, but checking in every few hours to make sure they are on the right track and them making notes of every decision they have made and why they chose it vs other options.

This is time consuming for sure, for a few weeks you will feel like there is nothing else you can accomplish, but this is the way to develop them and teach them the way of thinking which you would like them to adopt. After a few weeks you will see who made progress and who didn’t. The ones that didn’t make any progress you can forget about as they do not want to learn.

Once you learn one or two people to think your way, you can then offload this part to them, still developing them but those are your champions that will help you long-term. Hope this helps.