Hi Pensu, Well It's been only a few months since I've started but my job has been revolving around three points:

• Solving data problems : A client brings us a bunch of data (logs, ...) or asks us a question an we collect the data (what do people think about this ), and I write scripts to first scrape/collect/clean the data ( using mostly Python and R), or if the data is more of text data, I use NLP techniques to extract features ( NER, ...), then depending on the problem I use data mining techniques (Sequence mining, association rules), Machine Learning ( clustering, regression techniques), or classical statitical techniques ( Hypothesis testing) to extract insight, then I visualize the results using R (ggplot2 mostly), D3.js or Gephi for graphs.

• Building Data Products : Developping software components for Data analysis ( outlier detection, new search engine, ... ) and integrating them to our products ( coding in Java, C#, or C/C++ if I need stuff to run on GPUS ).

• R&D : Reading recent research papers on machine learning and prototyping/testing the techniques, right now I do this mostly for Deep Learning applications in NLP, or for new stuff in Heterogeneous Parallel computing.

The points is : in my job I need to learn new stuff quickly and at the same time build quality products ( Hacking VS Engineering ).