Ander Garro

WORK HISTORY

EDUCATION

SKILLS

ABOUT ANDER GARRO

I have over 4 years of experience working in computational science and 2 year of experience in the Data Engineering, managing, and deploying Bigdata + AI solutions. Currently, I have been working as a Data Engineer in a well-known RD company called IKERLAN. I have been performing both, Data Engineer and Scientist duties, developing data solutions for production industry and retail companies based on the development of AI models. Performed work has gone in the line of anomaly detection over time series and images and sales prediction.I worked as a Data Finance Engineer through a consulting firm (GFI) for the well-known Spanish bank BBVA before I joined IKERLAN. I developed data models which aimed to preserve data quality over ETL processes. Before, I worked as a Research Assistant in the University of Queensland, developing a programing tool which implements mathematical models in python-spark using the finite element method which the aim of solving any kind of boundary conditions problem. Previously, I was the Scientific Research Assistant of the Visual Monitoring Camera (VMC) instrument onboard a mission of the European Space Agency, Mars Express.I consider myself as a person with great capacity for teamwork, constant and with willpower at the time of performing activities that require effort. Thanks to my experience in Brisbane (Australia) which enabled myself to get involved in a multicultural atmosphere I have developed the ability to adapt to different environments. I have resolutive capacity, leadership and I manage well the moments of stress or a lot of work. I am very ambitious, and I am always willing to learn new skills.I am always interested in listening to colleagues, friends, or simply interesting and creative people, so do not hesitate to contact me if you want to connect.Competencies: Data Science: Integration of Deep Learning architectures (CNN, LSTM, RNN.), Econometric Models (Autoregressive schemes as SARIMAX, ARD, VAR, ARCH,…) and Classic Machine Learning algorithms.Data Engineer: Python/Scala/R, Notebooks (Jupyter/Google Colab), Version control (GIT, Subversion, GitBash, Tortoise), Data Modeling (Power Designer), Data Processing (Spark/Dask), Data Flow (kafka/storm), Distributed File Systems (HDFS), IaaS-PaaS (Specially AWS but also GCP), Model Deployment ML-Flow, Orchestrator (Airflow), Time Series Framework (Influx, kapacitor, Grafana,…) and databases (SQL, Postgress, MongoDB).Others:Basics in Java/HTML/XML, Fortran, C++, shell scripting, Geospatial software (QGIS).