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Natural Language Processing Researcher
Kaixo! ("Hello" in Basque) I am a passionate data scientist and natural language processing (NLP) researcher, a proficient Python programmer and AWS machine learning specialist. Currently I work at RoZetta Technology, a Sydney based company focused on providing big data management and analytics solutions in various domains and with over 20-year experience in financial market data. I work on the design and development of data engineering and machine learning pipelines to help generate valuable data assets and actionable insights. In addition, I am an Adjunct Researcher at the University of Technology Sydney (UTS), where I collaborate with Prof. Massimo Piccardi's NLP research group and co-supervise PhD students. I have publications in top NLP conferences and journals (e.g. TACL, ACL, NAACL , COLING, PAKDD, IEEE TAI). Previously I obtained a PhD in machine learning and NLP at UTS (2020) and a degree in Telecommunications Systems Engineering at the University of Navarra, Spain (2016).
University of Technology Sydney
Doctor of Philosophy (Ph.D.), Machine Learning and Natural Language Processing
January 1, 2017 – January 1, 2021
University of Michigan
Exchange Program - 2015 Fall semester, Computer Science
January 1, 2015 – January 1, 2015
University of Navarra
Degree in Telecommunications Systems Engineering, Undergradued
January 1, 2012 – January 1, 2016
University of Technology Sydney
Postdoctoral Research Fellow
June 1, 2025 – Present
Sendatu Therapeutics
Co-Founder
February 1, 2024 – Present
Sydney, New South Wales, Australia
University of Technology Sydney
Adjunct Fellow
November 1, 2020 – June 1, 2025
RoZetta Technology
Data Scientist and NLP Researcher
July 1, 2020 – June 1, 2025
Sydney, New South Wales, Australia
UNSW
Casual tutor at the Univerity of New South Wales
June 1, 2018 – October 1, 2018
Sydney, Australia
University of Technology Sydney
PhD Student in Machine Learning and NLP
January 1, 2017 – November 1, 2020
Capital Markets CRC Limited
NLP researcher
July 1, 2016 – June 1, 2020
Sídney y alrededores, Australia
IXYS San Sebastian
Internship - Design of a Configurable Matching Network for the 2.4GHz band
June 1, 2015 – July 1, 2015
Zuatzu street, 3, 20018 Donostia - San Sebastian, Gipuzkoa
CEIT
Internship - Fostering Talent Program - Energy Harvesting
May 1, 2015 – June 1, 2015
Miramon Technological Park
ML Pipelines on Google Cloud
Coursera
June 24, 2026 – Present
Machine Learning Engineering for Production (MLOps) Specialization
Coursera
June 24, 2026 – Present
RDF and SPARQL Essentials
Udemy
June 24, 2026 – Present
AWS Certified Machine Learning – Specialty
Amazon Web Services (AWS)
June 24, 2026 – Present
Bayesian Methods for Machine Learning (with Honors)
Coursera
June 24, 2026 – Present
Think Like A Relevance Engineer - Elasticsearch/Solr
OpenSource Connections
June 24, 2026 – Present
Functional Programming Principles in Scala
Coursera
June 24, 2026 – Present
EGA
Eusko Jaurlaritza
June 24, 2026 – Present
Graph Analytics for Big Data
Coursera
June 24, 2026 – Present
Certificado Verificado de edX para el curso Enabling Technologies for Data Science and Analytics: The Internet of Things
edX
June 24, 2026 – Present
Cultural Fit Analysis
The candidate's background is heavily academic and research-oriented, with some entrepreneurial experience. This profile aligns well with roles requiring deep technical expertise, innovation, and problem-solving. However, the lack of diverse industry projects or explicit team-based software development experience might indicate a potential gap in fitting into a fast-paced, product-focused engineering culture without a strong research component. The target role of 'NLP Engineer' suggests a need for both research and implementation skills, which the candidate's profile supports, but the balance between the two is not fully clear.
Soft Skills & Operational Fit
The candidate's experience as a tutor and co-founder suggests leadership, communication, and problem-solving skills. The research background implies strong analytical capabilities and a structured approach to complex problems. However, specific operational fit details are limited without direct project descriptions or team collaboration examples.