April 25, 2023, 9:21 p.m. | /u/r4intr

Data Science www.reddit.com

I'm looking for clever solutions from seniors and leaders out there.

What processes/templates/tools do you have in place to reduce the iterative churn in your analyses and projects? We spend far too much time doing high-lift/low-return exploratory analysis with six time-strapped decision-makers involved because we haven't been able to cut through the noise and get to the actual question we're solving for. The ambiguity inevitably drifts down to the analyst team, who know the least of anyone about the goals …

analysis analyst churn communication datascience decision exploratory good iterative least low makers noise planning processes projects reduce seniors setup six solutions spend team through tips tools

AI Engineer Intern, Agents

@ Occam AI | US

AI Research Scientist

@ Vara | Berlin, Germany and Remote

Data Architect

@ University of Texas at Austin | Austin, TX

Data ETL Engineer

@ University of Texas at Austin | Austin, TX

Lead GNSS Data Scientist

@ Lurra Systems | Melbourne

Data Engineer - Takealot Group (Takealot.com | Superbalist.com | Mr D Food)

@ takealot.com | Cape Town