Hi, I'm Marco Vargas
Master in Big Data Applied & Business Analytics | Applied Mathematics | Systems Engineer.
Data Scientist | Data Engineer | Business Intelligence Specialist | Data Analyst
Bridging data-driven insights with visionary strategies, I navigate the nexus of data science, business analytics, and business intelligence, sculpting a future where innovation meets informed decision-making.
About Me
My Profile
With over a decade of mastery in Computer Engineering, I’ve cultivated a dynamic skill set spanning the realms of Data Science, Data Engineer, Business Intelligence specialist, and Data Analytics.
My journey through the data landscape has been diverse, encompassing roles such as Data Scientist, Data Engineer, Business Intelligence specialist, and Data Analyst; Each role has enriched my understanding of data storage, processing, and analysis, contributing to a comprehensive and holistic perspective.
At the core of my expertise lies the application of advanced statistical methods and cutting-edge machine-learning techniques. Armed with Python, R, and SQL, I dive deep into vast datasets to uncover intricate patterns and insights that drive strategic decision-making.
But data is only as valuable as the insights it yields. That’s why effective communication is at the heart of what I do. Whether crafting compelling reports or delivering dynamic visualizations through Tableau, Power BI, or Excel, I ensure that the story behind the data is conveyed with clarity and impact.
With a comprehensive toolkit encompassing Pycaret, TensorFlow, Hadoop, Spark, and more, I stand ready to tackle any data challenge with precision and expertise.
Join me on a journey where data isn’t just a tool; it’s the catalyst for innovation, transformation, and unparalleled success.Computer
Portfolio
A glimpse of the projects I've been working on
Models

Model for Employee Turnover Prediction
Model for Predicting Employee Turnover in an Organisation. Leveraging machine learning techniques and data analysis, this model has been developed to identify patterns and key factors influencing employee turnover. From data collection and cleansing to model construction and predictive evaluation, each step is meticulously outlined. Users can learn how to utilise this model to anticipate and address employee turnover, thereby potentially enhancing talent retention and organisational efficiency.
Click to view on GitHub

Optical Fibre Clustering Model
This machine learning model was developed to analyse the extensive optical fibre network of a telecommunications company and segment potential customers into groups or clusters with similar characteristics. The main objective was to optimise the deployment of the sales force by assigning each salesperson to the most suitable clusters based on their profile and experience.
Click to view on GitHub
Visualisation
Skills
Things I code with
Python, Pycaret, TensorFlow, Pyspark, Apache Spark, Databricks , SQL server, Teradata, Postgres, R, RStudio, Crontab, Hive, Advanced Excel
Artificial Intelligence and Machine Learning
Supervised Learning: Neural Networks, linear and logistic regressions, decision trees, support vector machines (SVM), Random Forest, AutoML (pycaret).
Unsupervised Learning: k-means clustering, principal component analysis (PCA).
Data Visualization
Power BI, Tableau, Python, Excel.
Testimonials
Contact
Contact me
+601 414677751
mavstecnico2@gmail.com
