Analysis of large data-sets to identify trends to allow appropriate business decisions.
Development of a web platform providing visualization and analysis of geo-spatial data.
Entirely comfortable in Linux, MacOS and Windows environments.
Used Git and Mercurial extensively in and out of work.
Proficient with Django and Flask web frameworks through my work at Ecometrica as well as personal projects.
Familiar with typical front-end technologies through working on a single-page application at Ecometrica.
Experience with MySQL and PostgreSQL databases; NoSQL databases MongoDB and Redis, and metric storage database Graphite.
Experience using AWS for database storage (RDS), caching (Elasticache), storage (S3), hosting (EC2) and task scheduling (Lambda).
Frequently used software such as Numpy, Scipy, Cython in my Masters' and PhD.
Familiar with complexity theory, algorithm analysis and data structures.
At ease using Hadoop ecosystem tools: Hive, Spark, Oozie, and Pandas.
Skilled making plots and dashboards using Matplotlib, Bokeh, d3.js, Grafana and Tableau.
Familiar with typical models such as regression, naïve Bayes and random forests. Experience implementing these with Scikit-learn, and H2O. Have also implemented neural networks for image classification using Tensor Flow.
Contributed to various projects, including Pandas, knitpy and Jupyter.