About me
Hello!
I'm Guido Prado, a data enthusiast currently in Chicago with a Master’s in Business Analytics from UIC and Bachelor’s in Industrial & Systems Engineering from SJSU.
My professional journey began in Brazil, right after I graduated, I started working for one of the country's largest retailers, Americanas SA, where I developed a lot of new skills despite the steep learning curve. There, I developed expertise in extracting, transforming, and loading (ETL) big datasets, creating interactive dashboards, and utilizing tools like SQL, Python, Google Data Studio (Looker), GCP, Big Query, Power BI, and DAX. These experiences increased my technical abilities and taught me the significance of conveying complex data insights in a digestible manner, a skill I leveraged to lead weekly cross-functional meetings, aligning departments with data-driven strategies. My departure from Americanas SA in early 2023 was due to my full-time Master’s program, which prohibited external employment in the US during the first year. Consequently, I accepted a Teaching Assistant role at UIC. Now eligible for work again, I am eager to apply my enhanced skills from the Master’s program, which deepened my data analytics expertise through projects utilizing SQL, R, Apache Spark, Tableau, and predictive machine learning models with Python, emphasizing both academic learning and practical application.
During my time at SJSU, I looked for opportunities to develop my soft and technical skills. This way I founded the Nova Junior Enterprise at SJSU, a consulting company aimed at fostering entrepreneurial projects within the university. This endeavor, alongside my attempt to launch my own application, provided valuable lessons in agile methodology, project management, and leadership.
Fluent in English and Portuguese, I am eager to bring my analytical skills, passion for innovation, and dedication to data-driven decision-making to new opportunities. I am a quick learner, adaptable to new environments and teams, and an open and collaborative professional looking forward to making impactful contributions wherever I go.
Now, I can’t leave out the hobbies, which include playing boardgames, an activity that satiates my competitiveness (when I win of course), recording a Podcast about movies, which has really helped me be more extroverted and to open myself a little more, and lastly, I consider being in the loop on technology to be a hobby just given the amount of time needed to be on top of generative AI and hardware products, such as phones, and pcs.
Skills Expertisse
Analytical Tools
-
Tableau
-
Power Point
-
Google Slides
-
Power BI
-
Minitab
-
Excel
-
Google Data Studio (Looker)
-
Google Sheets
-
Google Cloud Platform (GCP)
Programming / Database
-
SQL
-
Spark
-
R
-
Big Query
-
Python (Pandas, NumPy, Scikit-Learn, Matplotlib)
-
Machine Learning Models
-
Hadoop
Areas of Interest
Data Visualization
To understand data, we need to see it. It helps if it’s intuitive and good-looking, but if we create a story with it, we can make impactful decisions.
Predictive Modeling
Implementing machine learning to reach the art of predicting the future (or at least attempting to).
Business Intelligence
It’s not about having the data; it’s about how we use it to create actionable insights.
Data Quality and Management
It’s not just about avoiding data storage in CSV files; it’s about ensuring data’s accuracy, consistency, and reliability.
Timeline
Latest Projects
(Tableau, Python, ML Models, Excel)
-
Evaluated Random Forest and KNN models to predict flight delays using a US airlines dataset with 1M data points and 20 attributes.
-
Created a visual storyboard to analyze flight delays for Southwest Airlines, intuitively pointing out the main anomalies.
(Python, ML Models)
-
Utilized statistical and machine learning techniques to analyze over 220,000 data points from 52 sensors on an industrial water pump.
-
Tested 5 ML models and enhanced predictive maintenance in manufacturing by implementing a Multivariate Gaussian Distribution model, achieving high accuracy and efficiency in anomaly detection.
(Python, Spark, SQL, Filtering Models)
-
Developed a sophisticated movie recommendation system using Apache Spark, integrating collaborative (ALS), content, and demographic filtering techniques to handle over 1 million movie ratings, user data, and movie metadata for personalized suggestions.
(R, ML Models)
-
Tested 4 ML models to optimize Carped sales strategies, with the goal of converting old customers to new again. A Carpet sales database was used with over 5,800 instances and variables, with Random Forest having the highest accuracy among the models tested.