Samuel Kamande is a Data Scientist at Nielsen and his presentation will focus on “Paradigm Shift in Research”.
We caught up with him and he shared a lot about his work at Nielsen, some of the projects he has worked on like “Digital Divide project in Trinidad and Tobago in 2013”,thoughts on the future of Data Science and something on Baidu’s Deep-Learning System among other things.
We’d like to hear your story of how you got into data science. What motivated you to work in data science?
I am a statistician by training (MSc. Statistics, University of Nairobi). One person quipped that a Data Scientist is a statistician living in San Francisco or using a mac – By those definitions, I guess I am still a statistician. Transforming data into information, knowledge and insights has been the key source of motivation for me. In my 3 years of working with data, I have seen various clients across various industries and disciplines as well as internal management teams make important and inflectional decisions based on the insights deduced from small and large data sets. It has been fulfilling and has kept me going – solving problems, identifying opportunities, predicting the future in the midst of uncertainty – just to name a few. I have had the pleasure of working in a few positions that have exposed me to both practical statistics and programming, necessitated by the huge amounts of data involved. That has also constantly maintained my zeal. In the wide field that is Data Science, there is always something new to learn and try out every day.
How does a typical day as a Data Scientist at Nielsen look like? What tools and algorithms do you use often and which are your favorite?
A typical day for me involves supporting the Client Service teams …read more
Source:: r-bloggers.com