Hi there 👋

I'm Michael Madeira

I'm currently a data professional, doing my freelancing and enterpreneurial journey, driven by solving real life problems, either using statistical data analysis, extracting insights and visualize them on dashboards or implementing a Machine Learning end-to-end solution.

Currently I'm eager to learn more from the longevity and preventive health fields and contribute to practical solutions development by applying my data scientist skills.

Really excited to connect and share insights on performance and wellness with everyone interested on improving their health and life metrics overall.

Check my DS Portfolio

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Projects

- Real Estate Investment Recommendation System

Problem:

This project is a recommendation system for Real Estate companies based on insights extracted from exploratory data analysis, to answer to real estate common business questions:

1. Which houses should be bought and for what price?
2. Once its bought when it's the best time period to sell it and for what price?
3. To rise the housing selling price, the company should do a renovation. So what would be good renewal changes?

Solution:

Build a report to answer business questions based on the data analysis and some empirical rules.

Project repo: https://github.com/MikeMadeira/HouseSales-RecommendationSystem

- Credit Card Customer Segmentation

Problem:

Domain: International Bank is an international bank that provides financial products such as loans, checking accounts, savings accounts, investment options, credit cards and etc.

Business model: Lend credit to customers and earn some profit from yield rates applied to credit loans.

Every quarter of the year, leaders meet to decide the company's goals for the next 3 months. At this last meeting, one of the decided goals is to create a marketing strategy to address customers who use credit cards.

1. Create a client segmentation based on clear selection criteria.
2. Make the segments accesible to business teams.
3. Teach business operation teams how to use the solution.
4. Transfer knowledge to Data Scientists on International Bank.
5. Point 2 or 3 actionable insights and recommend each respective business leveraging actions for each client segment.

Solution:

(Working On) I've already done my first CRISP cycle and got some clustering results. Now I have to interpret them.

Project repo: https://github.com/MikeMadeira/Credit-Card-Customer-Segmentation