About me

Hi, I’m Felix — a data enthusiast who gets genuinely excited when messy, real-world data starts to make sense and tell a story. I love the full journey: extracting data, cleaning it, finding patterns, creating visualizations that non-technical people can actually use, and turning insights into decisions that matter.

Over the past few years, I’ve worked on real business problems: building pipelines to pull and analyze payment data from external APIs, digging into large datasets to understand user behavior, and developing end-to-end interactive apps that make data easy to explore and understand. Along the way, I’ve also explored the basics of machine learning (credit risk, sentiment analysis, image classification) and experimented with simple RAG + LLM projects.

I’m always learning. My goal is to grow into a well-rounded data professional — someone who can automate complete data pipelines, build robust data applications, and apply machine learning where it truly adds value.

I’m fully remote, based in Brazil, fluent in English, and open to exciting challenges anywhere. If you're building something data-driven and want someone curious, hands-on, and ready to jump in — I'd love to connect and hear about it.

Tools & Expertise

  • Python icon

    Python

    Core language for end-to-end data workflows, using Pandas to extract data from databases and external APIs (including Mercado Pago and Stripe), clean messy datasets, transform and reshape information, load results, and automate repetitive analysis tasks.

  • database icon

    Databases & Querying

    Proficient in MongoDB (MQL aggregations & pipelines) and SQL for extracting, querying, and analyzing large structured and unstructured datasets efficiently.

  • dash icon

    Dash Apps

    Building complete, interactive, and highly customizable dashboards from scratch using the Dash framework (Plotly backend), including full deployment on cloud platforms like Render for real-time access and sharing.

  • machine learning icon

    Machine Learning & AI

    Applying machine learning with scikit-learn (classical models), Keras/PyTorch (deep learning), and experimenting with LLM tools (OpenAI, LangChain) for tasks like classification, regression, sentiment analysis, RAG setups and AI-powered basic applications.

  • tableau icon

    Tableau Public

    Creating clean, interactive and business-friendly data visualizations and dashboards to communicate insights effectively to non-technical stakeholders (basic level).

  • R icon

    R Programming

    Statistical analysis, advanced visualizations with ggplot2, reproducible reporting using R Markdown and publication-ready HTML documents.

  • GitHub icon

    Git & GitHub

    Used for version control, managing repositories, and maintaining clean, traceable project history.

Daniel lewis
quote icon

Daniel lewis

Richard was hired to create a corporate identity. We were very pleased with the work done. She has a lot of experience and is very concerned about the needs of client. Lorem ipsum dolor sit amet, ullamcous cididt consectetur adipiscing elit, seds do et eiusmod tempor incididunt ut laborels dolore magnarels alia.

Resume

Experience

  1. Data Analyst - TranscribeMe

    2023 — Present

    As a Data Analyst at TranscribeMe, I worked on transforming raw product and payment data into actionable insights that helped teams make better decisions across the company. My day-to-day work focused on understanding user behavior, revenue patterns, and product performance.

    Some highlights of my work:
    • Designed and maintained end-to-end data pipelines using Python and MongoDB to analyze user behavior, payments, and product usage.
    • Built automated workflows integrating Mercado Pago and Stripe APIs to monitor revenue, detect fraud patterns, and track user retention.
    • Developed internal Dash applications that allowed non-technical teams to explore data securely and in real time.
    • Led the design of a reactivation workflow that increased the recovery of churned users by over 20%.
    • Worked closely with C-level stakeholders to define KPIs and align analytics with business objectives.

  2. Quality Assurance - Scale AI (freelance)

    2024 — 2025

    As a freelance Quality Assurance specialist at Scale AI, I contributed to improving the reliability and accuracy of Large Language Models focused on implicit code execution.

    My work involved:
    • Designing domain-specific questions to challenge and train LLMs on real-world coding scenarios.
    • Evaluating, correcting, and refining AI-generated responses to ensure correctness, clarity, and usefulness.
    • Using Python to test, debug, and validate generated code outputs.

  3. Machine Learning Trainee - Anyone Al

    March, 2024 — August, 2024

    During my time as a Machine Learning Trainee at Anyone AI, I worked on several end-to-end projects that helped me build a strong foundation in applied machine learning, from data preprocessing to model evaluation.

    Key projects included:
    • Credit Default Risk Analysis: Trained and evaluated multiple models on a dataset of over 350,000 transactions to predict loan repayment probability.
    • Vehicle Recognition and Classification: Built deep learning models using CNNs to identify vehicle brand and model from unstructured e-commerce images.
    • Movie Review Sentiment Analysis: Implemented sentiment classification on 50,000+ reviews using Word2Vec and Logistic Regression.
    • Product Review Classification: Trained word embeddings and sentiment models to detect positive and negative opinions in user reviews.

Education

  1. Telecommunication Engineering - Instituto Balseiro

    2016 — 2018

    Admitted through a highly competitive selection process to one of the most prestigious scientific and engineering institutions in Latin America. Although I did not complete the program, this period provided me with a solid foundation in mathematics, physics, statistics and probability, as well as analytical thinking — all of which have been essential to my professional development.

    This experience strongly shaped my problem-solving approach and intellectual curiosity, which later guided my transition into data analytics and machine learning.

  2. Telecommunication Engineering - Universidad Central de Las Villas

    2012 — 2016

    Began my academic training in Telecommunications Engineering, maintaining a high academic performance with a GPA of 4.7/5. This period laid the groundwork for my technical mindset and motivated me to pursue more challenging academic environments.

Certifications

  1. Machine Learning I

    Columbia University · 2026

    Covered core machine learning concepts such as linear regression, classification, clustering, and dimensionality reduction, with a strong focus on the mathematical foundations behind these methods.

    View certificate →

  2. Google Data Analytics Professional Certificate

    Google · Coursera · 2026

    Covered the full data analysis workflow: data cleaning, analysis, visualization, and communicating insights using real-world business scenarios.

    View certificate →

  3. Machine Learning Engineer

    Anyone AI · 2024

    Hands-on training in supervised and unsupervised learning, model evaluation, and practical ML applications.

    View certificate →

Portfolio

Blog

    Work in progress!

Contact

I’d love to hear from you!

Whether you have a question, a project in mind, or just want to say hi, feel free to drop me a message 👋

Contact Form