I am a freelance data scientist, assisting businesses in interpreting their data for real-world results. I am into data analysis, data visualization, and machine learning, focusing predominantly on pre analytics and post analytics work.

The subject of the actual data is of secondary importance to me-I begin by understanding the problem and the business need. Hence, the questions must be relevant; I also review whatever data is available and may occasionally be inclined to steer the data collection process. This is all considered to be the preanalytics phase and is so very important to meaningful work.

Once this is done with, I am all about cleaning and exploring the data while translating analytical techniques in Python, R, SPSS, or any type of SQL all for in search of pattern recognition, key questioning, and practically relevant insights.

I set about visualizing the results using Python libraries like Seaborn and Matplotlib or Power BI/Tableau, depending on whichever suits best. They are not fancy, mainly just straightforward images to aid decision-making.

I work on machine learning by implementing models to solve real problems in prediction, segmentation, or classification. The results are then always explained simply so the business can understand and implement whatever processes are required.

Post analysis, I work on solutions that ensure recommendations are neat and tidy: ready to be implemented and trackable in terms of bringing actual improvements.

The way I am is simple and practical: I want to see your data working for you.