CURRICULUM VITAE | JIDDU ALEXANDER BROERSMA
“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 bit.ly/jidduupwork. 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
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).
- 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%)
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)|
|rvest (Web scraping)|
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.
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.
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.