Sebastian Azuaje Pardo

“What do you do?”

“I use reliable data science to maximize efficiency and minimize business risks”

Skills and knowledge in:

Python, R, HTML, CSS, Tableau, Power BI
Excel, VBA, PostgreSQL, MySQL, SQLite, MongoDB
Flask, Django, Streamlit, Scikit-learn, Pandas, Matplotlib, Seaborn
GCP, AWS, Azure, Notion, Microsoft Project

What I used to do working in

Treasury @BritishAmerican Tobacco

Analysis of financial data, identification of potential risks
Creation of Dashboards in Tableau for internal and external operations
Collaboration with teams to make data-based decisions

Data Science Consultant @ COB MARKETING S.L

Predictive analysis using SQL databases and Python for telecommunications campaigns buying
Build an interactive dashboards in Power BI
Identification of areas of improvement and growth opportunities based on data analysis

Projects to challenge my skills

Route optimization and delivery time prediction for Amazon Pola Siero

Information of the new Center

I developed a machine learning model with data on traffic, weather, accidents and delivery times from 2011 to date from delivery companies in Spain, for which I had to extract the data using techniques such as webscraping, use of APIs and downloading. of files in various formats to transform and standardize the training data of my prediction model in Python. I then stored the prediction data in a PostgreSQL database and created a CRUD with FLASK.

Cover of the project made with GPT4

When is the best time to enter a bullet tournament in Lichess?

Lichess

I extracted the information from the various daily bullet tournaments played in Lichess for a rating of less than 2000 ELO points and performed EDA and visualization of the data to determine when the players’ performance is worst and at what time there are fewer people against them. compete guaranteeing possibilities to level up more easily. Using libraries such as matplotlib, seaborn, pandas and numpy.

Tournaments

Where I can find the best house price in Asturias, Spain?

Website

Through web scraping the first 10 pages I request access to the API from the web moderators who allowed me to download in real time all the information about the apartments for sale and rent in Asturias, to be able to predict future prices by sector and identify a purchasing opportunity.

Idealista

Credit Card Fraud detection

Developed and deployed machine learning classification models to identify fraudulent transactions. My work involved data preprocessing, feature engineering, and building models like logistic regression, decision trees, and random forests. I optimized model performance using techniques like cross-validation and hyperparameter tuning, ensuring high accuracy in detecting fraudulent activities while minimizing false positives. Additionally, I collaborated with business stakeholders to implement the models into production systems, contributing to reduced fraud losses and improved financial security.

Know more about me

Industrial engineer with a passion for data analysis and visualization. Strong technical skills in Programming, machine learning and dive deep looking to unravel insights meaningful from complex data sets and query optimization. Passionate about transforming data into compelling stories and tangible actions, I am ready to contribute to the success of data analysis projects in any industry. Let’s connect to explore how I can add value to your team.

Education

Industrial Engineering UCAB - Venezuela (May 2021)
DS4B Introduction to data science for business (December 2022)
Data Science Dicampus, SEPE - Spain (May 2023)

Languages I speak

Spanish (Native)
English (C2)
Russian (B2)