About Me

Tech Lead Data Scientist at NOS, currently leveraging machine learning and data science techniques to generate business value in the telecom field.

My main goal is to work on data science and machine learning applications to solve business problems. I have worked on different real-world problems, including task allocation/scheduling, predictive modelling, image processing and classification, natural language processing, customer churn and customer offer generation.

In my past experience as a researcher I have became skilled in machine learning, data cleansing, normalisation and visualization, and creative thinking. I have successfully worked in optimisation, supervised - classification and regression - and unsupervised learning tasks, across different domains. Over the course of my Ph.D. work, I focused on optimal management of electrical appliances in smart homes, in the presence of uncertain (future) demand and generation.

I have experience with Python and its main data science libraries (Numpy, Scipy, Pandas, Scikit-Learn, TensorFlow, Matplotlib, Seaborn, Statsmodels, Jupyter), R, MATLAB, SQL, Java, JavaScript, C/C++, Bash scripting, Git, DVC and HTML/CSS. I have also worked with different machine learning and data science algorithms, including Gaussian Processes, Artificial Neural Networks, Support Vector Machines, Hierarchical and K-Means Clustering, PCA, LDA. Finally, I have experience with mathematical programming, in particular integer and mixed-integer linear programming, and well-known open source solvers such as SCIP or GLPK.

Experience

  • Tech Lead Data Scientist, NOS SGPS.
    - Responsible for the technical part of an offer generation projet (propose new packages/additives/etc for individual customers)
    - Monitor, plan and implement developments in the project from a technical side
    - Advocate for good software development practices and code consistency across different developers

  • Data Scientist, NOS SGPS.
    - Ensuring periodic deliveries with updated predictions/inference from a trained model
    - Exploratory data analysis and planning aiming to propose pilot project

  • Lead Data Scientist, Nokia.
    - Lead Data Scientist for 1 key area in the team
    - Working on Data Science projects involving predictive modelling, image processing and classification, scheduling and natural language processing tasks
    - Industrialization of data science projects

  • Data Scientist, Nokia.
    - Working on Data Science projects involving predictive modelling, image processing and classification, scheduling and natural language processing tasks
    - Industrialization of data science projects

  • Scientific Research Grant (June 2017 - July 2021). PhD Research Grant, funded by "Fundação para a Ciência e Tecnologia" (FCT), working on the PhD Thesis during the Information Science and Technology Doctoral Program at the University of Coimbra.
    - Uncertainty-aware resource allocation (stochastic programming, mixed-integer linear programming)
    - Historical dataset collection (SQL, Python, data cleaning, inspection and normalisation)
    - Probabilistic model development, tuning and evaluation (Gaussian processes, Quantile regression, Cross-Validation)
    - Merit award: Engineer Lecturers Award, Ordem dos Engenheiros -- Região Centro (2019)

  • Invited Assistant Professor (Feb 2017 - Aug 2019), at the Department of Informatics Engineering of the University of Coimbra. Courses taught:
    - Data Analysis and Transformations (linear and non-linear systems, time-frequency analysis and time series analysis). Course of the second year of the Bachelor's Degree in Informatics Engineering
    - Introduction to Programming using Java. Course of the Acertar o Rumo Postgraduation Cycle

  • Grant Researcher (Feb 2017 - May 2017). Project "Controlo de Abastecimento de Águas", Laboratory of Hydraulics, Water Resources and Environment, Department of Civil Engineering, University of Coimbra.
    - Automate data collection, processing and visualization (Django, PostgreSQL, JavaScript, Data Normalisation, PCA)
    - Pattern discovery and evaluation (Hierarchical and K-means clustering, dynamic time warping)

  • Grant Researcher (September 2015 - Feb 2016). Project "Incentivo CISUC 2014", Laboratory of Industrial Informatics and Systems, Department of Informatics Engineering, University of Coimbra.
    - Development and validation of rule-based control systems
    - Best Paper Award: 4th Experiment@ International Conference (2017)

  • Grant Researcher (August 2014 - August 2015). Project "EI0169", Laboratory of Industrial Informatics and Systems, Department of Informatics Engineering, University of Coimbra.
    - Offline and online time-series outlier detection and accommodation (MATLAB, Python)
    - Remote laboratory for introduction to programming and control systems courses (Java, Apache Struts 2)
    - PyDAQmx-Interface, remote control of three-tank system (Python~2.7, National Instruments 6008, 6009 boards)

  • Invited Assistant Professor (Feb 2017 - Aug 2019), at the Department of Informatics Engineering of the University of Coimbra
    - Introduction to Programming using Java. Course of the Acertar o Rumo Postgraduation Cycle

Education

  • Ph.D. in Information Science and Technology, Faculty of Sciences and Technology, University of Coimbra, Portugal (Sep 2016 - Jun 2021)
    - Thesis: Adaptive Supervisory Framework for Cyber-Physical Systems
    - Final Classification: Summa Cum Laude (Highest Praise)

  • M.Sc. in Informatics Engineering, Technology, Faculty of Sciences and Technology, University of Coimbra, Portugal (Sep 2014 - Jun 2016)
    - Final Classification: 17/20
    - Thesis: Flood Management in Urban Drainage
    - Relevant Coursework: Artificial Intelligence, Evolutionary Computation, Experimental Methodologies, Machine Learning, Systems Modelling and Analysis, Pattern Recognition

  • B.Sc. in Informatics Engineering, Technology, Faculty of Sciences and Technology, University of Coimbra, Portugal (Sep 2011 - Jun 2014)
    - Final Classification: 17/20
    - Merit award: Top 3% students (2012 and 2013)
    - Relevant Coursework: Algebra, Databases, Distributed Systems, Programming, Mathematical Analysis, Statistics

  • Coursera, Natural Language Processing with Probabilistic Models. Online Course (April 2023)

  • Coursera, Natural Language Processing with Classification and Vector Spaces. Online Course (Feb 2023)

  • Udemy, Feature Selection for Machine Learning. Online Course (Jun 2020)

  • Udemy, Feature Engineering for Machine Learning. Online Course (Mar 2020)

Skills

  • Machine Learning
    - Regression, Classification, Supervised Learning, Unsupervised Learning, Optimisation
    - Time series, Mathematical Analysis, Feature Engineering, Feature Selection, Natural Language Processing
    - Data Cleansing, Normalisation and Visualization, Hypothesis Testing, Cross-Validation
    - SVMs, ANNs, Deep Learning, Gaussian Processes, Random Forests, Capsule Networks
    - Hierarchical and K-Means Clustering, PCA, LDA
  • Programming
    - Python (Numpy, Scipy, Pandas, Scikit-Learn, TensorFlow, Matplotlib, Seaborn, Statsmodels, Jupyter)
    - R, Scala, MATLAB, SQL, Bash, C/C++, Java, JavaScript, Git, DVC, S3, HTML, CSS

Languages

  • Languages
    - Portuguese (Native)
    - English: Certificate in Advanced English (C1) and First Certificate in English (B2)

Diplomas & Events

  • Merit award, Engineer Lectures Award, Ordem dos Engenheiros - Região Centro (2019)

  • Best Paper Award, 4th Experiment@International Conference - exp.at’17: "Flood Management in Urban Drainage: Contributions for the Control of Water Drainage Systems using Underground Barriers" (June 2017)

  • Master's Degree Diploma in Informatics Engineering (University of Coimbra 2016)

  • Bachelor's Degree Diploma in Informatics Engineering (University of Coimbra 2014)

  • Certificate of Advanced English (C1) - Feb 2011

  • First Certificate in English (B2) - Aug 2009

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