Roland Dunn

Experienced engineer & manager [Python/Django/ElasticSearch/JS/Postgres/Pandas/Numpy and much, much more]

London, United Kingdom

Summary

I am an experienced developer, manager, lead engineer, currently working at Timetric (http://www.timetric.com/).

Most recently, I have worked on Attent.io, a project that involved significant-scale analysis of news articles, involving Python, ElasticSearch, Redis, Django, Postgres, JavaScript and experimental sentiment analysis, clustering, elements of machine learning, and much, much more.

I am: a UK/Canadian citizen. I have conversational Italian. I run a bit, and play cello.

Languages:

English, Italian

Favorite Python Packages:

collections requests python-dateutil beautifulsoup

Experience

1) Currently:

Currently working as a lead engineer at Timetric (http://www.timetric.com/) having spent around three and a half years working on, and building up Attentio (http://www.attentio.com/), a news and trend analysis service aimed at corporate businesses.

Timetric is a provider of market research and analysis services for businesses, Attentio is a research project investigating whether any news services could be automated or semi-automated, and whether any new features could be created through the use of technology. The result has been a service similar to https://signalmedia.co/media-monitoring/ except on a smaller scale, one that has been integrated into a number of Timetric's market analysis products (e.g. see https://goo.gl/S8WwF6 for an example of integration). To give some sense of scale, at its peak the service was analysing around 200,000 news articles / day.

Technically, the work has involved investigating scalable methods of identifying those news articles relevant to specific sectors (using some basic machine learning/clustering), and examining how to summarise mentions of companies, topics, brands in a meaningful and useful way, e.g. how to measure volume of mentions, assess sentiment, explain the measures, etc. Lots of discussions around what is accurate, what is accurate enough, how can accuracy be measured and explained and more.

Technology-wise the work included Python and Django development, Elastic Search, Postgres, Redis (and Redis Q), NGinx, Twisted Python, Scrapy, Python NLTK, sentiment analysis and others (including use of Ansible, Vagrant and more).

2) Previously:

Before Timetric I worked in the digital media industry for a number of few years, primarily in technical positions, constantly involved in development of one kind or other. I had a period of eight years or so of working whilst juggling being an at-home-dad, been the technical director of a small agency, a search consultant & developer/data-miner, founded a small UK/Swiss collective (http://www.refinedpractice.com/), and co-wrote an eBook on data visualisation (see https://www.goodreads.com/book/show/18160462-developing-a-d3-js-edge). I also have some experience of giving public talks (see http://www.cloudshapes.co.uk/about/talks/).

I have a little website http://www.cloudshapes.co.uk/ that contains a set of experiments written in a mixture of D3js, Python, and in one case a JS game engine. For example, a visualisation of tweets featuring vocabulary from the UK/Irish TV series "Father Ted" from the character "Father Jack": http://www.cloudshapes.co.uk/labs/tweets-featuring/father-hackett/.

I've uploaded a small chunk of Python code from a small project of my own (used to track values and trading volumes of crypto-currencies) to https://bitbucket.org/rolandino/example/src.

I am currently working my way through a set of Coursera courses in data science & machine learning (https://www.coursera.org/specializations/data-science-python), and would be keen to continue the course(s) and apply the skills I'm gaining in a real-world setting.

Brand-names wise, I have worked at Microsoft & Sony, and in terms of management, managed teams both virtual and real of various disciplines and sizes.

I have worked remotely, in offices, worked with people around the world (e.g. when writing the D3 book), and am comfortable being self-disciplined and self-motivating.

3) Next:

I'm looking for something interesting and stimulating, something problem-solving based perhaps:

- I've enjoyed working at scale with large quantities of data.

- Interested in machine learning and AI.

- I'm quite fascinated by Fintech, particularly crypto-currency and blockchain related work.

In terms of location and work style:

- Entirely remote, or Central/North London with flexible working.

4) Personal:

UK/Canadian citizen. Almost intermediate-level Italian. Aspiring runner. Play cello.

Skills

Amazon Web Services (AWS), Django, Elasticsearch, JavaScript, Machine Learning, Natural Language Processing, PostgreSQL, Redis, Scrapy, Vagrant, Visualization, Web Scraping