The role was advertised as Data Scientist, but the interviews were more aligned with data engineering and data analysis. No predictive modeling or machine learning questions were asked. The process began with an informational call with a hiring manager, focused mostly on if I understood what economic consulting was and interest in the field. The first round included two interviews: one behavioral and one “technical,” which involved walking through how to populate an Excel sheet from hypothetical tables. Despite being told to expect a coding assessment in Python, R, or SQL, no programming was tested. Next was a take-home case study to design a pipeline that could consolidate data from multiple CSV/Excel files for business analysis. The final round consisted of three interviews centered on my resume, goals, and interest in consulting, with no technical questions. Overall, my experience was neutral since the interview process seemed poorly organized at times. It felt like the interviewers at times were lost on what to ask since the data science team is an collections of either data engineers or data analysts, making their background not directly applicable to my more traditional data sci background.