Let's Dive Into Analysis
I’ve experience with Pandas in Python to perform marketing analysis and predict future growth for tech startups and scaleups
Data Analysis Process
With the aim to help scaleups achieve sustainable growth through predictive analysis, my process involves three steps: 1) data preparation; 2) data segmentations and visualisation; 3) A/B testing & predictions.
Data Cleaning
Importing & Cleaning data sets
Insights
Segmentation & Visualisation
Predictions
A/B Testing & Regression Analysis
Why do I love pandas?
I started working with pandas in 2021 and it soon became my favourite data analysis programming language. I love pandas as it provides a simple but intuitive way to manipulate and analyse structured data in no time. I can easily import various data formats, including CSV, Excel, SQL databases, and more, enabling seamless data integration from product, finance and marketing teams.
What some of my past employers loved about me
M. Teichert
Nico particularly excelled on the performance marketing optimisation side where he had clear, actionable suggestions on running new experiments to lower the CPA and his experience in the field clearly became apparent.
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