Dr Saúl Vargas Sandoval

Data Scientist

About Me

Data Scientist at ASOS, fashion recommendations it is.


My PhD thesis, under the supervision of Professor Pablo Castells at the Autonomous University of Madrid (Spain), is titled "Novelty and Diversity Evaluation and Enhancement in Recommender Systems". As a byproduct of the thesis, I developed RankSys, a Java 8 Recommender Systems framework for novelty, diversity and much more.


An up-to-date list of my publications is available in my Mendeley profile.

ASOS RankSys

Contact Information

-
Location

ASOS.com
Greater London House
Hampstead Road
London NW1 7FB, UK

Telephone

Mobile: +44 750 721 4179
(I do not take calls from unknown numbers)

Experience and Education

EXPERIENCE
ASOS

Data Scientist

ASOS, March 2017 - Present

Fashion recommendations.

Mendeley

Senior Data Scientist

Mendeley, June 2016 - February 2016

Working in the Data Science team lead by Kris Jack.

Mendeley

Data Scientist

Mendeley, November 2015 - June 2016

Working in the Data Science team lead by Kris Jack.

University of Glasgow

Research Assistant

University of Glasgow, January 2015 - November 2015

Working on the SUPER-FP7 project with R. McCreadie, C. Macdonald and I. Ounis.

UAM

Teaching Assistant

Universidad Autónoma de Madrid, 2012 - 2014

Doing research towards my PhD thesis under the supervision of P. Castells and teaching lab sessions for undergraduate courses.

Yahoo! Labs

Research Intern

Yahoo! Labs Barcelona, Summer 2014

Working with R. Blanco and P. Mika.

Telefónica Research

Research Intern

Telefónica Research Barcelona, Summer 2013

Working with L. Baltrunas and A. Karatzoglou.

University of Glasgow

Visiting Researcher

Univeristy of Glasgow, Summer 2012

Working with R.L.T. Santos, C. Macdonald and I. Ounis.

UAM

Research Grant FPI-UAM

Universidad Autónoma de Madrid, 2011 - 2012

Doing research towards my Master's thesis under the supervision of P. Castells.

EDUCATION
UAM

PhD in Computer Science

Universidad Autónoma de Madrid, 2012 - 2015

Supervised by Professor Pablo Castells.
"Novelty and Diversity Evaluation and Enhancement in Recommender Systems".

UAM

MSc in Computer Science

Universidad Autónoma de Madrid, 2010 - 2012

Universität Bielefeld

Exchange Student

Universität Bielefeld, 2009 - 2010

As part of the Erasmus Programme.

UAM

BSc in Computer Science / BSc in Mathematics

Universidad Autónoma de Madrid, 2005 - 2010

Skills

Recommender Systems

Recommender Systems

The main research topic during my PhD and my specialty as Data Scientist. Interests: novelty and diversity, collaborative filtering, learning to rank and scalability. Creator of RankSys, a Java 8 Recommender Systems framework. My research has been published and presented in conferences such as RecSys, SIGIR and WSDM.

Information Retrieval

Information Retrieval

I have done work on the diversification of web search results and query auto-completion for mobile search. I have experience in working with the open source search engines Elasticsearch and the Terrier. My work on this research topic has been published and presented in relevant conferences such as SIGIR and WSDM.

Efficient and Scalable Programming

Efficient and Scalable Programming

I care about developing efficient and scalable implementations of algorithms and systems. For this purpose, I have extensive experience in profiling, optimising and parallelising Java code, and in programming with distributed computing platforms and languages (Scala, Spark, Hadoop, Pig, Giraph).

Web development

Web development

Designing easy-to-access and user-friendly interfaces for your systems and algorithms is a requirement nowadays. Therefore, I have dealt with web technologies for designing good-looking interfaces (Bootstrap, jQuery) and powerful backends accessed via RESTful web services (Dropwizard) for prototype validation and showcasing.