| Programming Python |
Advanced proficiency in Pandas, GeoPandas, SciKit-Learn, TensorFlow, Pytorch, keras, Matplotlib, NumPy, SciPy, SQLAlchemy, Seaborn, Bokeh, SciKit-Image |
| Programming R |
Advanced proficiency in RStudio, Shiny, tidyverse, Parsnip, bayestestR, sparklyr, keras, dygraph, forecast |
| Modelling |
Advanced experience in statistical modelling, time series analysis, supervised and unsupervised machine learning algorithms, currently implementing solutions in reinforcement learning (intermediate) |
| Geospatial Analysis |
Advanced skills in geospatial machine learning, professional proficiency in ArcGIS, QGIS and OpenGeos (Python) |
| Big Data & Databases |
Proficient in SQL, MongoDB (NoSQL), Spark (pyspark and sparklyr) |
| Experimental Design |
Strong background in designing and implementing A/B tests, and Bayesian statistics |
| Languages |
Fluent in English and Spanish (native) |