About Me

I am a data scientist with strong mathematical background and a PhD in climate sciences, currently at Booking.com. I have experience analysing petabyte scale dataset and delivering key results to business stakeholder as well as prototyping and productionizing machine learning solutions at large scale.

Contact Details

Alessandro Mozzato
96 Fokke Simonszstraat
Amsterdam, 1017 TK
(+39)340-6312491
mozzatoale@gmail.com

Download Resume

Work

Booking.com

Data Scientist • June 2017 - Present

Analysis of large data-sets to identify insights to inform business decisions.

  • Querying petabyte-scale data using Hadoop and related particularly Spark to answer business questions
  • Working with decision-makers to suggest practical actions, and ways to quantitatively test their success
  • Extensive experience with A/B testing at scale, analysing experimentation practices, testing and developing appropriate metrics
  • Build a web application for analysis and visualisation of a large textual dataset

Enel

Data Scientist • September 2016 - June 2017

Research and development of machine learning algorithms for anomaly detection and predictive maintenance.

  • Worked on machine learning models on time series
  • Developed an anomaly detection model for power plant monitoring
  • Developed and deployed a webapp for model monitoring and live validation

IZSV

Data Scientist (Consultant)• August 2015 - September 2016

Analysis of geospatial data and development of predictions for virus spreading.

  • Geospatial analysis of metereological and environmental data
  • Developed a machine learning model for virus diffusion prediction

Education

National Oceanography Center, Southampton

Ph.D. Climate Sciences • 2013 - 2017

Can huge submarine landslides affect thermohaline ocean circulation and climate? Developing climate models to study strong perturbation of the Arctic Ocean circulation.

  • Code written mainly in Python, interfaced with model written in Fortran.
  • Close collaboration with climatologists, field geologists and phisical oceanographers.
  • Interdisciplinary work of interest to audiences ranging from mathematics to geology.

University of Padova

Master of Science Applied Mathematics 110/110 cum laude• 2011-2013

Final thesis: A mesh adaptive algorithm for numerical incompressible Navier-Stokes equations

  • Stochastic Analysis
  • Stochastic Methods for Finance
  • Numerical Methods for Data Analysis
  • Partial Differential Equations
  • Dynamical Systems

University of Lille

Master 2 - Erasmus Programme• 2012-2013

University of Padova

Bachelor in Mathematics• 2008-2011

Final Project: The Exponential Radon Transform

Skills

I have experience analysing large dataset using big data tools such as Hive Spark and Oozie and well as delivering key results and insights to drive business decisions. Experience delivering data visualizations and dashboards using Matplotlib, Bokeh, d3.js, Grafana and Tableau.

I developed and deployed machine learning algorithms for anomaly detection as well as an application for text analysis on a large corpus of documents. I also worked on recent deep learning topics such as word embeddings, Word2Vec and Generative Adversarial Networks.

I am familiar with web development concepts covering back-end in python using Flask and standard front end with HTML/CSS and javascript from my work at booking.com and personal projects.

  • Machine Learning
  • Data Analysis
  • Python
  • Hadoop-Spark
  • Tensorflow
  • Web Development

Experiences

Research Vessel Pelagia

Onboard Scientist • July 2014

Involved in seismic and bathymetric data collection, visualisation and processing in a one-month research cruise in the Arctic.

INRIA

Software Researcher • March 2013 - June 2013

Development and validation of mesh adaptive techniques for fluid dynamics problems.

Relevant Courses

CS50's Web Programming with Python and JavaScript

Harvard University on edX • Ongoing

Web development fundamentals with Python and JavaScript

Deep Learning Specialization

deeplearning.ai on Coursera • 2018

Five courses specialization by Andrew Ng on Deep learning using Python, Tensorflow and Keras.

Machine Learning

Stanford University on Coursera• 2016

Machine learning course by Andrew Ng covering fundamental machine learning topics ranging from linear models, trees to neural networks.

Data Science at scale

University of Washington on Coursera• 2016

Three course specialisation using: MapReduce on Pig and Python, Machine Learning on R, SQL. Final project Predict building abandonment, using Python and Tableau on a real world dataset