Career Science – building a career out of data science consulting
What do companies really need and how can you exceed their need as a data sciene professional?
The 21th century sexiest job sure seems … hyped. Companies say they want to hire data scientists when in reality they want to have data solutions in production.
Data scientists seem more in demand than ever but it’s hard to find a resume of a newcomer that doesn’t say Kaggle or Machine Learning (Udacity/Coursera/anyOtherMOOC[tm]).
This talk will be a story of what skills end up making a difference. I will discuss things to be aware of when you want to work as a data scientists. Things like;
– the difference between a data analyst and a data scientist
– technologies come and go: hadoop, spark and now tensorflow
– low tech solutions often beat high tech: for loops vs. deep learning
– stable pipelines are more important than the algorithm
– the understanding of the problem is more import than the algorithm
– most profit is made from experiments that are allowed to fail
– how to hire a data scientist if you aren’t one
– how to prevent not getting hired for a data science role
– suggestions for activities outside the office: conferences, meetups, projects
Data Scientist, GoDataDriven
Vincent taught himself programming four years ago while being a digital nomad in Latin America. Now he is a data scientist at GoDataDriven, founding chair of PyData Amsterdam, preferred Rstudio training partner and organiser of the Applied Machine Learning Meetup in Amsterdam. The blog he started over at koaning.io has also been getting a lot of attention. Thing can happen fast if you set your mind to it.