Florents T.

I use mathematics and machine learning to analyze & explain data. When the machine doesn't learn, I do it the old-fashioned way: I use my brain and do my own learning instead.

I consider my skillset to lie somewhere in the intersection between Machine Learning, Data Engineering and Software engineering . (that is to say, in other words front-end is not my thing).

I've worked with all the cool Python libraries through the whole "data lifecycle": crawling data, queuing systems, db management, training ML models, API design and deployment management (Ansible mainly)
Libraries include: Pandas, NumPy, Scikit-Learn, Matplotlib, python-rq, celery, requests (of course), Selenium and many more.
In web development I have developed web apps in Flask and Django.

In terms of data engineering I have production experience with most of the major database systems: I've managed Hadoop/Spark, MongoDB and ElasticSearch clusters and Redis, PostgreSQL and MySQL deployments. Occasionally I teach corporate seminars on such topics.

I have also extended experience in crawling & scraping all sorts of websites.

I am comfortable not only on the command line but in business meetings as well - where business and technical objectives should meet. I have consulted many international companies in the areas of predictive analytics, market analysis and marketing budget allocation, mainly in the telecoms and retail industry. Occasionally, I also teach corporate courses & seminars on software engineering, data analysis and big data systems engineering.

I've also research experience on such topics and a couple of publications as well. You may have a look here
http://dl.acm.org/citation.cfm?id=2627773 and http://ceur-ws.org/Vol-1558/paper38.pdf