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“Fundamentally learning about the world through data is really, really cool.” Hadley Wickham

‘Can you give me another sum to solve?’ (Mag ik nog een sommetje?) I asked my mother. As a small child I preferred doing maths and eating cheese over watching telly and eating candy. I had normal hobbies too, I played football every day.

Not so much has changed since then. What makes me feel great still this day is a good mix of solving logical problems, tasting delicious food and being active outdoors. The first one makes my living.

As a theoretical physicist I am trained to understand how complex systems behave mathematically, causation more than correlation.

I’m building up a strong strategic system that to tackle data problems effectively. It uses a range of tools that tell you what to do next. It starts from the very question you want answered and ends after that the implementations paid off.

Recent Work Experience

  • Freelancer through Upwork, May 2016 – Present

Please see my job history and feedback at If you do not have an account I can share a screenshot of job history and feedback on request.

  • Technology Officer at Prakti, Tamil Nadu (South India), May 2014 – Jan 2016

The last two years as the Technology Officer of a cookstove manufacturer in South India one of my main tasks was to develop a data driven product development set-up. This system included field measurement tools in combination with scientific testing equipment and managed to accurately reproduce real life conditions in the lab. It was a large scale complicated system, where proper science and data made the real difference; turning guessing and poking in the dark into a strategic data driven approach.

  • Energy Auditing and Project Management at Auroville Consulting, Tamil Nadu (South India), June 2013 – February 2014

Relevant Experience

I have taken a list of professional (paid and unpaid) trainings, participated in several data hackathons and actively participate in several data and programming related Meetups.


  • Master R Developer Workshop by RStudio with Hadley Wickham (Amsterdam 19-20 May 2016).

Hackathon events

  • Transport Lab Hackathon (June 2016), Second prize.
  • Farm Hack Reusel (June 2016), Second prize.
  • Postbank Hackathon Cologne (June 2016), SAS prize
  • Smart Benutten Urban Data Hack by Data Science Amsterdam (21-22 May 2016), First prize.
  • WFP Hackathon organised by DataMission (14 May 2016), Third prize.

Online Course Certifications

  • Machine Learning, Stanford University (Andrew Ng) (100%)

From the Johns Hopkins Data Science Specialisation:

  • Developing Data Products (100%)
  • Practical Machine Learning (100%)
  • Regression Models (100%)
  • Reproducible Research (98.3%)
  • R Programming (97.6%)
  • Data Scientist Toolbox (100%)

Datacamp courses:

University Education

Master of Physics in Theoretical Physics, Sussex University, Second-class honours, upper division

Besides introductory courses in various programming languages I also took a course in Neural Networks.

After my graduation I continued with my research group to co-author a paper: Microfabricated Ion Traps, Contemporary Physics 52:6, Marcus D. Hughes, Bjoern Lekitsch, Jiddu A. Broersma and Winfried K. Hensinger.


I have a wide skillset covering many aspects of data science including strategic, programming, analytical, and reporting skills.


I’m strong with most of the tidyverse packages:

Core Vector operations Data Import Modelling
tibble hms (times) feather modelr (modelling with pipeline)
purrr stringr (strings) DBI (databases) broom (tidying models)
tidyr lubridate (dates) haven (SAS, SPSS, Stata)
dplyr forcats (factors) httr (APIs)
ggplot2 jsonlite (JSON)
readr readxl (Excel)
rvest (Web scraping)
xml2 (XML)

Visualisation and Reporting

I am a Shiny App developer. These beautiful interactive web applications fully written in R are highly popular. I can develop the kind of products as shown on the RStudio Shiny gallery.

I’m highly skilled with gplot2 and many of its extensions.

Personally I work in R Notebooks (the new R Markdown) 90% of the time. My work is reproducible and can be exported to pdf, html and word as a standard.

Machine Learning

I have a great understanding of machine learning models. I have the mathematical understanding of most common models (Neural Networks, PCA, SVM, RandomForest, Regression, Clustering). I have gathered a large set of tools to ensure effective machine learning work flows. Currently I’m testing several R packages for their strengths and weaknesses to add to my set of tools.

Advanced Programming

With Advanced R and the Master R developer workshop I (May 2016) will make big steps forward in my skills to do functional programming, object oriented programming and metaprogramming, as well as building R Packages.

Data Science Strategy and Tools

Two of my favourite topics so far I learned from Bernard Marr and Andrew Ng.

SMART data (Bernard Marr) is a tool that makes sure data science is implemented as a means to improve projects/business. I have applied it beneficially in my position as Technology Officer.

Through Andrew Ng I’ve learned a set of tools to work very effectively. They are used in combination with standard models and including: ceiling Analysis, pipeline, learning curves and error analysis.