Want to know more about my work? Take a look at my professional portfolio.
I’m a business intelligence developer and data analyst with experience working in behavioral science designing experimental and quasi-experimental evaluations of programs with social impact. I’m excited about using my skills in experimentation, Python, SQL, Power BI and Tableau to develop models and visualizations that deliver insights to improve lives.
I used data on Uber & Lyft rides to predict demand and assess the profitability of rides. The goal was to inform drivers about the times of the day, weekdays, location and weather conditions when they can expect higher demand, and provide a strategy to maximize profitability. I used Python for the analysis, and developed a Power BI dashboard with insights and actionable recommendations.
Check my analysis on this Jupyter Notebook
See my insights on this Power BI Dashboard (link to file on Google Drive) or see the dashboard in PDF
House prices are influenced by many factors. Some of them are fairly well-known to the general public, but many factors are not known to most home buyers, impairing their ability to negotiate house prices accurately and fairly. I developed a regressive model to predict final sale price of houses based on known house characteristics with Microsoft Excel, and created a technical slide deck to report on process and results.
See more information on this PowerPoint Presentation
Check my analysis on Microsoft Excel
ChemCorp is a mock company that produces chemical products. I analyzed business data on market segments and product performance with the goal of informing a new customer strategy, understanding what market opportunities exist to explore and what products are underperforming. Developed a Power BI dashboard to report on the results and provide actionable insights on investment and divestment opportunities over segments and products.
The AEMR is a mock energy market regulator responsible for looking after the domestic energy network in the USA. I analyzed data about energy outages to understand the nature of these outages and identify the most unreliable energy providers. Used Tableau to develop a dashboard with actionable insights for corrective measures.
Southwater Corp is a mock company that owns a series of water dessalination plants. I used data on water pump failures to develop a regressive model to predict these failures, with the goal of reducing plant’s downtime and manitenance costs. Performed the analysis in Python, and created a presentation with the results and suggested and preventing metrics.
E-mail address: diogomiguelbsantos@gmail.com
LinkedIn profile: https://www.linkedin.com/in/diogo-santos/