Vinicius Brenck, Developer in Brasília - Federal District, Brazil
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Vinicius Brenck

Verified Expert  in Engineering

Full-stack Developer

Brasília - Federal District, Brazil
Toptal Member Since
November 4, 2022

Vinicius is an experienced and passionate full-stack web developer and data scientist with Python and Django as his stronger skills. He's also a project leader who loves building data-driven web applications that help clients thrive, from startups to big corporations. Vinicius has an extensive business administration and finance background that helps him understand client needs better and deliver the best results-oriented solutions.


Python 3, Django, Tailwind CSS, Vue, Pandas, Selenium, Beautiful Soup...
Brazil's Federal Revenue Service
SQL, Hue, Apache Impala, Python 3, Jupyter Notebook, Big Data, Leadership...
Arquitetura de Eventos
Python, Python 3, Django, Django ORM, Bootstrap, Bootstrap 3+, jQuery, HTML...




Preferred Environment

Django, Tailwind CSS, Vue, SQL, APIs, Jupyter Notebook, Python, CSS, JavaScript, Django REST Framework

The most amazing...

...tool I've developed from scratch to deployment is an app for a small business that controls daily sales and provides financial reports to the managers.

Work Experience

Full-stack Web Developer and Data Scientist

2020 - PRESENT
  • Built a stock market screener using API data to create put or call email alerts based on trading strategies of graphical and technical analysis.
  • Created a real estate investment fund screener using web scraping to send regular HTML email reports with trading opportunities based on predefined strategies.
  • Implemented a fundamental analysis stock market screener using web scraping to send scheduled HTML emails with trading opportunities based on publicly available companies' data and indicators.
  • Designed and developed a social network marketing tool using Selenium to automate Instagram profile posts by managing messages, followers, and likes.
  • Integrated a face detection plugin to check if Instagram user profile pictures indicate a potential business or personal account.
  • Obtained 16th place in a Kaggle machine learning competition to develop a model to predict client churn probability in telecommunication contracts using supervised learning.
Technologies: Python 3, Django, Tailwind CSS, Vue, Pandas, Selenium, Beautiful Soup, Jupyter Notebook, HTML Templates, HTML Email, Web Scraping, Web Development, Web App Development, Full-stack, SQL, Finance, Full-stack Development, Heroku, Deployment, PostgreSQL, Microsoft Excel, CSS3, HTML, Python, CSS, JavaScript, Front-end, Back-end, jQuery, Architecture, Software Design, Amazon Simple Email Service (SES), Django ORM, Bootstrap, Bootstrap 3+, REST, REST APIs, APIs, Django REST Framework

Tax Inspector and Data Scientist

2010 - PRESENT
Brazil's Federal Revenue Service
  • Detected anomalies in government payments to private entities using unsupervised learning.
  • Selected taxpayers suspected of committing fraud for examination from large databases.
  • Obtained fifth place in a national data challenge to forecast taxpayers' behavior on compliance.
  • Acted as the IT project leader in implementing the Foreign Account Tax Compliance Act in Brazil and served as the country's delegate for the OECD's working party number 10 on exchanging information and tax compliance.
  • Provided mentorships and training on SQL and data analysis for experienced coworkers.
Technologies: SQL, Hue, Apache Impala, Python 3, Jupyter Notebook, Big Data, Leadership, IT Projects, IT Project Management, Project Leadership, Data Science, Machine Learning, Unsupervised Learning, Supervised Learning, Microsoft Excel, Scikit-learn, Data Collection, Anomaly Detection, Supervised Machine Learning, Python, Architecture, Software Design, REST, REST APIs, APIs, Team Leadership

Full-Stack Web Developer

2021 - 2022
Arquitetura de Eventos
  • Developed a full-stack web app from scratch to deployment for a small business, providing control of sales, clients, suppliers, and financial structures, as well as custom reports like balance sheets, future cash flow, and profit margin statements.
  • Designed the user interface of the financial reports according to the client's requests.
  • Implemented the application's responsiveness to make it presentable in all screen sizes and devices.
  • Configured and deployed the app to Heroku, setting up the production environment and the PostgreSQL database with scheduled weekly backups.
Technologies: Python, Python 3, Django, Django ORM, Bootstrap, Bootstrap 3+, jQuery, HTML, CSS, Heroku, PostgreSQL, Architecture, Software Design, Front-end, Back-end, SQL, Web Development, Deployment, JavaScript, Full-stack, Full-stack Development

Credit Risk Analyst and Account Manager

2005 - 2010
  • Performed credit risk analysis for loans based on credit scoring and behavior scoring models.
  • Managed clients' business and personal accounts on multiple banking-related subjects such as investment, loans, insurance, and trade.
  • Led a small team of coworkers handling client service and satisfaction.
Technologies: Risk Models, Accounts, Finance, Loans, Customer Data, Investments, Microsoft Excel, Team Leadership

Arquitetura de Eventos Management App
I developed a full-stack web application for Brazil's event hosting and production company. The web app consists of a management software that fully controls the business, its clients, suppliers, and financial structures. It also offers multiple custom reports for the administrator user, including balance sheets, individual profit margin reports for each event, future cash flow analyses, and payables and receivables statements.

The app was developed from scratch to deployment using Django and HTMX. I was in charge of creating the custom financial reports and the banking statements section.

Anomaly Detection in Government Payments to Private Entities
I created an anomaly detection model as the final study for my postgraduate specialization degree in data science and big data.

Using publicly available datasets in the Brazilian government's transparency portal,, the model detected around 3,000 anomaly transactions among 4.9 million entries between 2018 and 2020. I used three unsupervised learning anomaly detection algorithms to compose a final voting model: k-NN, isolation forest, and autoencoder. The anomalies detected do not imply fraudulent or irregular transactions but payments substantially different from most government transfers to private entities. The system considers entity and transaction features for the anomaly score.

Real Estate Funds Screener App
I built an investment screener app for monitoring real estate funds, known as REITs in the US. The screener uses web scraping to gather information from specialized sites and publicly available data to create and send email alerts of trading opportunities for a small group of investors, according to predefined strategies.

Stocks Fundamental Analysis App
I created an app that runs a scheduled script to monitor public companies' data. It makes HTML emails with trading alerts based on fundamental analysis indicators, including the dividend payout ratio, free cash flow, dividend yield ratio, debt-to-equity ratio, and return on equity. The data is obtained by web scraping publicly available balance-sheet information. After that process, the alerts are submitted to a small group of investors.

Instagram Profile Automation App
I developed a social media marketing app using Selenium to automate an Instagram profile and its posts by managing messages, followers, and likes. The automation provides charts informing the possible origins of new followers and allows programming strategies for obtaining new interactions according to specific business rules. It also includes a plugin to identify if the related parties are a most likely business or personal accounts by checking the profile picture using face detection with a multi-task, cascaded, convolutional neural network (MTCNN).

Kaggle Telecommunications Churn Challenge
I obtained 16th place in a Kaggle machine learning competition to develop a model to predict client churn for a telecommunications service. Based on preexisting labeled data, the model uses a supervised learning algorithm of choice to indicate whether clients are prone to churning.
2020 - 2022

Postgraduate Degree in Computer Science

Pontifical Catholic University of Minas Gerais (PUC Minas) - Belo Horizonte, MG, Brazil

2003 - 2007

Bachelor's Degree in Business Administration

Federal University of Minas Gerais (UFMG) - Belo Horizonte, MG, Brazil


Data Science



Pandas, Beautiful Soup, Django ORM, REST APIs, Vue, HTMX, Scikit-learn, Matplotlib, jQuery, NumPy


Apache Impala, Hue, Microsoft Excel, Seaborn, Plotly, Amazon Simple Email Service (SES)


Django, Tailwind CSS, Bootstrap, Bootstrap 3+, Selenium, Django REST Framework


SQL, HTML, Python, CSS, Python 3, CSS3, JavaScript


Data Science, REST, Anomaly Detection


Jupyter Notebook, Heroku




APIs, Machine Learning, Unsupervised Learning, Supervised Learning, Big Data, Investments, HTML Templates, HTML Email, Web Scraping, Full-stack Development, Leadership, IT Projects, IT Project Management, Project Leadership, Supervised Machine Learning, Web Development, Web App Development, Full-stack, Front-end, Back-end, Business, Financials, Administration, Risk Models, Accounts, Finance, Loans, Customer Data, Deployment, Data Collection, K-nearest Neighbors (KNN), Variational Autoencoders, Isolation Forest, Team Leadership, Instagram Marketing, Bots, Architecture, Software Design

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