Matteo Manca

Data Scientist



I am a data scientist, with background in Computer Science, and several years of experience working on data-driven solutions in cross-functional teams. I have experience collecting, analysing, mining large datasets and implementing machine learning models. I thrive on challenges and I like to use data to support decision making and to solve real world problems. I taught data science related courses in different masters and I am program committee member in some of the main Data Mining conferences. I obtained my PhD in computer science from the University of Cagliari (IT), with a thesis on the study and implementation of recommendation approaches for the social media domain.


  • Data Mining
  • Recommender systems
  • Machine learning
  • Ranking algorithms


  • PhD in Computer Science, 2014

    University of Cagliary (Italy)

  • MD in Computer Science, 2009

    University of Cagliary (Italy)

  • BSc in Computer Science, 2007

    University of Cagliary (Italy)


Data Science

  • Machine Learning Frameworks (Scikit-learn, H2O)
  • Deep Learning Frameworks (Keras)
  • Data Analysis and Visualization Libraries (Pandas, NumPy, SciPy, Matplotlib, Seaborn, GGplot)
  • Relational Databases and Big Data (Mysql, PostgreSQL, Sqlite, PySpark)
  • Geographical Analysis Tools (GeoPandas, Folium, Leaflet, Carto)


  • Python (libraries scikit-learn, Pandas, Numpy, etc)
  • Pyspark, R, SAS, SQL (mysql, Postgres, SQLite) bash scripting
  • Knowledge of Scala, Matlab, C, C++, Objective-C, Java, Javascript (JQuery), PHP, HTML and CSS LaTeX

Soft Skills

  • communicate results (technical and non-technical audiences)
  • Problem-solving attitude
  • Willingness to learn and master newt echnologies and techniques
  • Ability to work independently and in a team.
  • Project management and team leading.

Recent Experience


Senior Data Scientist


Dec 2019 – Present Barcelona (Spain)
Responsibilities include:

  • Analysis of digital trace data and query logs
  • Application of data-mining, computational methods and implementation of machine learning models.

Senior Research Data Scientist

Eurecat, Technology Center of Catalonia

Feb 2019 – Dec 2019 Barcelona (Spain)
Responsibilities include:

  • Principal Investigator and Work package leader in European Projects.
  • Participation in Grant proposals (e.g., H2020).
  • Main Data Scientist in multiple private and public projects.
  • Application of data mining and computational methods to digital trace data.
  • Implementation of predictive models.

Data Scientist

Zurich Spain

Feb 2018 – Feb 2019 Barcelona (Spain)
  • Data analysis to quantify risk and support business decision making.
  • Implementation and validation of predictive and statistical models.

Research Data Scientist

Eurecat, Technology Center of Catalonia

Sep 2015 – Jan 2018 Barcelona (Spain)
  • Participation in European Projects.
  • Applying data mining and computation methods to digital trace data.
  • Implementing predictive models.


Tutorial on Data Analysis of Mobility Behaviour Data

Methods and Tools to Analise Mobility Data

Gender inequalities in political participation a study of the 2017 UK general elections on Twitter.

we analyze a dataset of 4.5 million tweets related to the UK general elections of 2017 to investigate the gender composition of the …

Urban Patterns and Citizen Participation Geographical Data Analysis of Decidim Barcelona.

I presented our study about Decidim Barcelona, i.e. a participatory process implemented by the city council of Barcelona to enroll the …

From Social Science to Computational Social Science, Is Web Data the Key to a More Effective Analysis?

Opportunities, challenges and open issues related to the use of new sources of data in Computational Social Science.


  • Honorable mention at The Web Conference 2018 (WWW) with the demo paper “BarcelonaNow: Empowering Citizens with Interactive Dashboards for Urban Data Exploration”.
  • Best paper award runner up at the 3rd International Conference on Data Management Technologies and Applications (DATA 2014) with the paper “Mining user behavior in a social bookmarking system – A delicious friend recommender system”.
  • Best paper award at the 3rd International Conference on Advances in Information Mining and Management (IMMM 2013) with the paper “Producing friend recommendations in a social bookmarking system by mining users content”.