Lillian Pearson has a timely and excellent post on gaining real world programming experience in data science.
Lillian lists 3 options:
- In your current job, look for opportunities to carry out data analysis and code for automation or improved efficiency. An example from a colleague (mine, not Lillian’s) is learning and using Excel VBA to create a user form for operators on a shop floor to enter information on the fly. As data is entered, the spreadsheet calculates cycle times, scrap/reject counts, and yield percentages. The point is to use whatever tool – Excel, Python, R, Java – that does the job and to add value to your existing enterprise.
- Find an internship. Lillian stresses looking locally and not re-locating for something as temporary as an internship. An example of a productive internship is Jorge Fernandes‘ internship at the The Hartford in Connecticut, that led directly to his being hired.
- Find freelance work through marketplaces and social media. Lillian lists some good examples.
I want to add a fourth option, the one that proved very successful for Jorge Fernandes in landing a job with Pratt & Whitney: find an empowering project of interest to you, and to others, and discuss your progress on this project on LinkedIn. Jorge’s project was to carry out a spatial analysis of police reports in Brockton, MA, using R. But he didn’t just do this and keep it to himself: he discussed the project, and his progress on it, on a LinkedIn page, and so got the attention of recruiters.
The moral: be pro-active. Be visible. Follow your interests and passions and broadcast them, on social media, especially on LinkedIn, where recruiters are looking for people just like you.