Carlos Miguel Pereira
Verified Expert in Engineering
Data Science and Machine Learning Developer
Carlos has a solid track record in designing and implementing data-driven solutions, including advanced predictive modeling and optimization algorithms. His academic and professional background also brought him extensive knowledge of software development, data engineering, data visualization, and project management skills. Besides having a Ph.D., Carlos has done two postgraduate courses, one general management program, and a vast number of certifications and technical courses.
Git, Visual Studio Code (VS Code), MacOS
The most amazing...
...project I have implemented was a customer churn predictive model with potential savings of €1 million per year.
Senior Manager, Data Science
- Led the data science team composed of a mixture of junior and senior data scientists and data engineers.
- Built roadmaps and prioritized work for the data science team.
- Mentored and coached the team to grow both technically and professionally.
EDIT. Disruptive Digital Education
- Taught data science and deep learning modules in the data science and business analytics program.
- Defined the course content for the data science and deep learning modules.
- Created slides and material for the data science and deep learning modules.
- Assessed the students of the data science and deep learning modules.
Data Science Consultant
- Took responsibility for end-to-end architecture, implementation, and delivery of one MVP to an energy solutions company and another to an electricity company.
- Leveraged mobility and geospatial data to predict the best locations for EV Charger installation across the UK.
- Estimated electricity network headroom geospatially.
Data Science Manager
- Delivered a data strategy and roadmap of use cases for a large Benelux group.
- Defined candidate qualifications and conducted interviews.
- Built internal best practices and company awareness.
- Defined roadmap of advanced analytics and reporting use cases.
- Developed Churn and next order predictive models and deployed them in containerized web applications.
- Built ETL pipelines using AWS services and created dashboard reports.
- Performed deep-dive business analysis such as LTV, repetition patterns.
Lead Data Scientist
- Created a model to predict Churn and dunning to prioritize welcome calls.
- Developed a model to predict equipment defects to avoid inefficient replacements.
- Created a model to predict technical recurrences to reduce customer attrition.
- Built a model to predict customer satisfaction, NPS, and voice of the customer (VoC) scorings.
- Created a model of sentiment analysis for customer surveys.
- Performed several developments for web scraping, including sites, forums, Facebook, Reddit, and LinkedIn.
- Led and mentored more than ten people. Some projects included predicting the recurrence of telecom problems, developing an intelligent call routing, predicting billing service requests and errors, and building chatbots for robotic process automation.
- Defined roadmap of analytical use cases for the department.
- Managed collaboration with universities and co-supervised MSc students.
- Defined cases and conducted interviews for the trainee program.
Team Lead Machine Learning Engineer
Center for Computer Graphics
- Led and mentored the machine learning team including Ph.D. students.
- Developed a business analytics system for the chemical sector of a large multinational company.
- Applied machine learning algorithms for the textile sector of a large national company.
- Involved in the initial phase of the development of a scalable and automated machine learning system for the security sector of a large national company.
- Developed a recommendation system for the retail sector of a national company.
- Interacted directly with clients and other stakeholders.
- Led technical writing of multi-million euro funding proposals.
- Involved in the creation of the Collaborative Laboratory ProChild CoLAB against Poverty and Social Exclusion.
Institute of Telecommunications
- Proposed novel system architectures for connecting e-health devices directly to the Internet.
- Created models and optimizations for e-health devices connecting directly to the internet.
- Wrote research papers and co-supervised MSc students.
Institute of Telecommunications
- Designed energy- and latency-aware scheduling schemes to improve battery life on smartphones.
- Optimized and created a packet transmission scheduling model.
- Created a smartphone battery consumption model taking into consideration the different transmission technologies.
- Designed and benchmarked IoT middleware platforms and mobile gateway applications for a telecommunications company.
- Applied distributed computing and meta-heuristics to explore resource efficiency gains for multi-homed wireless devices.
- Characterized and created a model of radio frequency interference in vehicular networks.
- Wrote research papers, was involved in international collaborations, and co-supervised MSc students.
Institute of Telecommunications
- Developed resource allocation and decision algorithms leveraging advanced coding techniques.
- Characterized and created a model of packet collisions in vehicular ad-hoc networks.
- Wrote research papers and was involved in international collaborations.
Customer Churn and Payment Default Prediction
Predict Equipment Defects
Predict Customers' Next Order
Sentiment Analysis and Topic Classification of Customer Surveys
Predict Customer Satisfaction
Predictive Model of Technical Recurrences
Python, SQL, R, Java, Bash, C, C++
LightGBM, Hadoop, Flask
Matplotlib, Pandas, Scikit-learn, XGBoost, TensorFlow, Keras, PySpark
Tableau, MATLAB, PyCharm, Jira, Git, Seaborn, Confluence, Microsoft Power BI, GitHub, R Studio, Subversion (SVN), JetBrains, IntelliJ IDEA, AutoML, NGINX
Data Science, Business Intelligence (BI), Management, ETL, Linear Programming, Azure DevOps, Constraint Programming
Windows, Linux, RStudio, Oracle, Azure, AWS Lambda, Jupyter Notebook, Android, Docker, Amazon Web Services (AWS), AWS Elastic Beanstalk, Zeppelin, Databricks, Visual Studio Code (VS Code), MacOS
Optimization, Data Analysis, Programming, Data Analytics, Algorithms, Machine Learning, Mentorship, Team Management, Monitoring, Predictive Modeling, Research, Large-Scale Computing, Development, Modeling, R&D, Technical Writing, Distributed Systems, IoT Protocols, Deep Learning, Roadmaps, Metaheuristics, Web Scraping, Big Data, Data Engineering, Data Visualization, Dashboards, Natural Language Processing (NLP), eCommerce, Consulting, Text Mining, Statistics, Data Strategy, GPT, Generative Pre-trained Transformers (GPT), Scrum Master, Wireless, Software Development, Software Architecture, Software Design, Grid Computing, Operations Research, Startups, A/B Testing, Leadership, Geospatial Data, Geospatial Analytics, Electric Vehicles, Cloud, Recommendation Systems, Experimental Design, Tutoring, Instructor-led Training (ILT), Artificial Intelligence (AI), Machine Learning Operations (MLOps), Azure Databricks, Computer Vision, Business
Databases, Apache Hive, DBeaver, JSON, Redshift, Google Cloud
MBA Essentials in Management
The London School of Economics and Political Science - London, UK
Oxford Executive Leadership Programme in Leadership
Saïd Business School, University of Oxford - Oxford, UK
General Management Program in Management
Católica Lisbon School of Business and Economics - Lisbon, Portugal
Postgraduate Programme in Business Intelligence and Analytics
Porto Business School - Porto, Portugal
Ph.D. in Electrical and Computer Engineering
Faculty of Engineering of the University of Porto - Porto, Portugal
Azure AI Fundamentals
Azure Data Scientist Associate
Deep Learning Specialization
Tableau Desktop Specialist
Data Visualization with Tableau Specialization
Data Engineering, Big Data, and Machine Learning on GCP Specialization
Certified Scrum Master
Complete Guide to TensorFlow for Deep Learning with Python
Spark and Python for Big Data with PySpark