Rodrigo Heck, Developer in Lisbon, Portugal
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Rodrigo Heck

Verified Expert  in Engineering

Data Science Developer

Lisbon, Portugal
Toptal Member Since
January 28, 2022

Rodrigo is a data scientist with experience in data communication and analysis, interactive data visualization, and web development. He focuses on developing solutions with AI, natural language processing, and computer vision and embedding them in user-friendly applications. Rodrigo enjoys building transformative systems using the best technology and solving problems by delivering quality solutions using algorithms, data, and creativity.


Michael Sullivan & Associates LLP
Python, Flask, React, TypeScript, OpenAI GPT-4 API, LoRa, Text Retrieval
Data Science, Python, SQL, Google Cloud Platform (GCP), Recommendation Systems
Wispr AI
React, Flask, Python, Amazon Web Services (AWS), Socket.IO




Preferred Environment

Jupyter Notebook, Visual Studio Code (VS Code)

The most amazing...

...project I've developed is a platform that gathers different Brazilian fashion eCommerce platforms in one website powered by a sophisticated search algorithm.

Work Experience

AI Developer

2023 - PRESENT
Michael Sullivan & Associates LLP
  • Developed a retrieval augmented large language model (LLM) that could leverage internal data to provide better answers in a chatbot setting.
  • Built a chatbot platform from scratch, setting up both front- and back-end architectures.
  • Developed an internal method for information retrieval composed of multiple steps.
Technologies: Python, Flask, React, TypeScript, OpenAI GPT-4 API, LoRa, Text Retrieval

Data Scientist

2022 - 2023
  • Automated the process of campaign poster creation by finetuning stable diffusion on proprietary data.
  • Leveraged GPT family models to automatically generate important insights from text data.
  • Created dashboards analyzing social media information about the company.
  • Helped to put in place a recommendation algorithm based on user demographics and platform interactions.
Technologies: Data Science, Python, SQL, Google Cloud Platform (GCP), Recommendation Systems

Full-stack Developer

2022 - 2022
Wispr AI
  • Developed a real-time dashboard able to display the signal from physical sensors.
  • Created a back-end system that allowed low latency data communication in a continuous setting using sockets.
  • Implemented a system to record data from physical sensors to build a dataset for machine learning training.
Technologies: React, Flask, Python, Amazon Web Services (AWS), Socket.IO


2021 - 2022
  • Developed a platform that enabled users to do simple searches that return posts related to the input on social media.
  • Used zero-shot learning to leverage AI for text classification.
  • Implemented the back-end structure, including the APIs, databases, and file storage.
  • Developed a customizable dashboard that allowed the user to investigate data returned from social media.
Technologies: React, Python, PyTorch, Generative Pre-trained Transformers (GPT), GPT, Natural Language Processing (NLP), Flask, Firebase, Cloud Firestore, Firebase Realtime Database, JavaScript, Web Scraping, APIs, Gunicorn, Hugging Face, Firebase Web SDK, Docker, Data Engineering, Front-end, Back-end, Full-stack, HTML, CSS, Amazon SageMaker, Amazon, Amazon Web Services (AWS), Artificial Intelligence (AI), Data, Containers, JSON, GitHub

Data Scientist

2020 - 2021
James Tip
  • Elaborated visually compelling dashboards that could help the clients better navigate their data.
  • Maintained and improved the code used to provide purchase recommendations to the clients.
  • Created new methods to identify and avoid stockouts.
Technologies: R, SQL, RStudio Shiny, Statistical Methods, Statistics, Python 3, Python, React, Data Analysis, Data Analytics

Data Scientist

2020 - 2020
Data Science Brigade
  • Conducted thorough statistical analysis on large datasets of clients.
  • Elaborated presentations that contained the most critical findings from our investigations.
  • Applied machine learning to automatically discover what most impacted the success of the client's business.
Technologies: Python, Data Visualization, Data Analysis, Jupyter Notebook, Linear Regression, Python 3, Machine Learning, Deep Learning, TensorFlow, Long Short-term Memory (LSTM), Pandas, NumPy, Plotly, Data Analytics, Analytics, Scikit-learn, BigQuery

Junior Data Scientist

2018 - 2020
  • Used natural language processing and other artificial intelligence methods to assess the NPS of client companies, resulting in a better synthesis of consumer sentiment on social networks.
  • Built interactive visualizations in dashboard formats and automatic reports to communicate valuable information internally and externally.
  • Developed Bayesian models that could measure the impact of interventions in a real-life scenario or the non-experimental environment.
Technologies: R, Python, Keras, Bayesian Statistics, Naive Bayes, Deep Learning, Machine Learning, Web Scraping, Twitter API, Python 3, PyTorch, Dashboards, Data Analysis, Net Promoter Score (NPS), Clustering, Topic Modeling, Convolutional Neural Networks (CNN), Market Research, Marketing Research & Analysis, Analytics, Scikit-learn

Shelves Identification

A system that can show the brand prevalence in an image of a supermarket shelf.

I developed the AI algorithms necessary to segment and classify each product and the platform that would enable the client to manually label the brands for training purposes. All solutions were encapsulated in a simple-to-use API that received an image and returned the distribution of products and brands.

Automatic Reports

An R Shiny report that allowed our clients to interact with their summarized data.

Our company collected a lot of social media comments about our clients. Still, most of the interaction they had with this data was by checking the overall sentiment displayed as a single number.

My intention with this project was to automatically generate a Shiny application that offered all the important information they wished to know in a single place. They had access to previously calculated metrics and could interact with the graphs and comments, conduct customized searches, and generally have a better overall understanding of their data.

The clients to which we introduced this solution were satisfied with the tool. They enjoyed this guided but not static experience to know what happened over a certain period regarding their social media presence.

Consulting Marketplace
A platform that connects consultants and clients. I was the CTO and developed all the functionalities available, combining NLP techniques for the search algorithm and front and back-end skills to deploy an easy-to-use layout. Consultants have the ability to receive proposals to connect, they can create live events and sell tickets, and they can offer their skills to specific companies. These features required the correct implementation of a flexible payment gateway. In this case, I used Stripe. The development of an online conference solution to in-platform video connection; the use of front and back-end frameworks to build everything up (Flask, Firebase, and React), and the deployment of the system on cloud servers (AWS).

Dataset Gathering from Multiple Surveys

A Shiny app able to access different types of datasets and convert all of them into a unified format. Surveys conducted by a research team were pretty similar, but there were some idiosyncrasies that made the merge between different datasets somewhat complicated. This app allowed the team to map all the questions into the same structure and download a single merged dataset.

Internal Chatbot for Law Firm

This was a project for a law firm that wanted to enhance their internal knowledge database, hoping to offer a similar experience to what we all enjoy with ChatGPT. First, it required building a retrieval model to get the relevant documents, then tweaking GPT-4 enough for it to understand what it is supposed to do with its context window, and, finally, building a compelling and beautiful interface for users to interact.


R, Python, Python 3, SQL, HTML, CSS, JavaScript, TypeScript


Flask, RStudio Shiny


Pandas, Keras, TensorFlow, Firebase Web SDK, NumPy, TensorFlow Deep Learning Library (TFLearn), Scikit-learn, React, PyTorch, Twitter API, Stripe, Stripe API, Stripe Connect API, Socket.IO


Net Promoter Score (NPS), Plotly, Amazon SageMaker, BigQuery, GitHub


Jupyter Notebook, Firebase, Visual Studio Code (VS Code), Docker, Amazon, Amazon Web Services (AWS), Google Cloud Platform (GCP)


Firebase Realtime Database, Cloud Firestore, JSON


Natural Language Processing (NLP), Dashboards, Hugging Face, Data Analytics, Market Research, Marketing Research & Analysis, Data, GPT, Generative Pre-trained Transformers (GPT), Probability Theory, Machine Learning, Data Analysis, Data Visualization, Statistics, Computer Vision, Web Scraping, Naive Bayes, Deep Learning, Clustering, Topic Modeling, Statistical Methods, Linear Regression, Long Short-term Memory (LSTM), Convolutional Neural Networks (CNN), Front-end, visNetwork, Artificial Intelligence (AI), Computer Vision Algorithms, Analytics, Generative Pre-trained Transformer 3 (GPT-3), Economics, Politics, Economic Analysis, Bayesian Statistics, APIs, Gunicorn, Data Engineering, Back-end, Full-stack, Containers, Jitsi, Data Structures, Recommendation Systems, Chatbots, OpenAI GPT-4 API, LoRa


Data Science, Text Retrieval

2014 - 2019

Bachelor's Degree in International Relations

Universidade Federal do Rio Grande do Sul - Porto Alegre, Brazil

2017 - 2018

Specialization in Urban Economics

University of Göttingen - Göttingen, Germany


MicroMasters in Statistics and Data Science

MITx on edX

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