Pros
Revenue Boost: I had a blast leading a project that boosted consumer revenue by a whopping 31.4%. We set up this cool data pipeline using BigQuery and Celonis that helped us analyze our finances smarter and ultimately make more money. Automation Genius: I also got to lead a project where we automated a bunch of processes using Jenkins and Airflow DAGs. We were dealing with a crazy amount of data – like 5TB a day! – but these automation tools saved us tons of time and made everything run smoother. Problem-Solving Pro: Oh, and there was this tricky problem with Excel data pre-processing that was eating up a bunch of developer time. But guess what? I swooped in with a Python and R solution that not only fixed the problem but also made us way more efficient. Mentorship: Plus, I had the chance to mentor some awesome data science interns, which was super rewarding. It was cool to share what I've learned and help them grow in their skills.
Cons
Revenue Boost: I had a blast leading a project that boosted consumer revenue by a whopping 31.4%. We set up this cool data pipeline using BigQuery and