I am geospatial expert by training currently transitioning into the world of data science. Within last 13 years I have worked on number of civil engineering industry problems including geodesy, precise positioning and GIS. Six years ago I transited back into academia.
I have completed my PhD at the University of Nottingham combining GPS with similar but terrestrial based positioning system to create precise (cm to dm level) positioning in areas of limited sky visibility. Technology I used was created by Australian start-up leading to my interest into disruptive technology, start-ups and data science. I think the first victim was Matlab - I ditched it for python and R.
I currently work at the University of Nottingham.
Data science is a blend of programming, statistics, industry specific knowledge, mixed with the lateral thinking and sparkled with the curiosity of the mind. In short, it is very exciting and actively developing - just check how many Ycombinator startups has data science at heart.
Data science is multi-disciplinary, using data analysis, lateral thinking and industry-related knowledge to create new insights. This is where PhD level analysis and interpretation skills come into play. Data science is not a magical black box. There is a lot of research, knowledge and hard work backing it up to make it successfully.
Want more information? Google for “sexiest job of the 21st century”, “data is new oil” or read Lin’s blog.
Still interested in me? Those links might help: