Long story short, I'm an applied statistician with four to five years of industry experience. Most of my work has been in the marketing vertical and has involved the use of SQL, R, and Python for model development and evaluation on medium sized data sets that required minimal cleaning.<p>After recently being let go from a big corporation that mischaracterized a role, I have begun applying for data scientist roles as I'm interested in taking my skill set in that direction. I've had a few interviews for data scientist roles over the past two weeks, but I've considered whether getting a data science internship would help add something to my resume. What do you think? Should I look for an internship at this stage in my career?<p>Thanks!<p>EDIT: I do not have a PhD. Background is an MA in social science discipline plus lots of late nights and weekends continuing to learn and develop my skills.
Make some showy data visualizations with R or MatPlotLib. Publish them somewhere with a link you can share. Even better if you can handle a little webdev, make something like one of these and really knock their socks off: <a href="http://d3js.org/" rel="nofollow">http://d3js.org/</a>. Have a resume website or fleshed out LinkedIn account that you can share.<p>Sign up on Kaggle (<a href="https://www.kaggle.com/" rel="nofollow">https://www.kaggle.com/</a>) and start participating in contests. Use this to refine your technique. If you do well in the contests, it will be noticed. Be awesome, tactfully, but publicly. Join their data science jobs mailing list and aggressively pursue leads. Make friends and participate in the community and forums.<p>You should also be attending events like ODSC (<a href="http://odsc.com/" rel="nofollow">http://odsc.com/</a>). Talk to data science people in your area, make connections.<p>Get very, very friendly with the features in NumPy. Keep your skills sharp and continue to build them.<p>You should get paid for what you do. Take charge of your fate.
Don't do an internship: you already have years of professional experience doing similar work.<p>In spite of what I call the so-called shortage for data scientists, getting a data science job is a pretty tough challenge. Read this post for a good description: <a href="http://treycausey.com/data_science_interviews.html" rel="nofollow">http://treycausey.com/data_science_interviews.html</a><p>Keep interviewing and applying for jobs. You will learn a lot about what exactly you want to do and eventually land on something.<p>If you are in or near one of the tech hubs in the US, I might recommend a data science bootcamp like those offered by Metis, or even an evening course like that offered by General Assembly. Such programs typically have connections with local industry and can help network.
Keep looking for a full time job as a data scientist.<p>Keep learning and polishing your skills while on your hunt.<p>Also look for contract positions, short term projects with companies, also look at doing a few data projects on your that might be interesting to employers.<p>An internship isn't going to look as good as a full time gig or even short term paid engagements.<p>Good luck in 2016 leveling up.
Most companies won't consider you for an internship if you're not a student. Age might be a factor but its not a big one. I am a 38 year old graduate student and I had no problem getting a paid internship for the summer. I'm not a data scientist, YMMV.
A data science internship won't help as much as a data scientist job. That will probably take longer to find than two weeks but less time than finding and completing an internship.<p>Since you are making it to the interview stage and have knowledge of typical tools, my gut tells me that an internship won't improve your resume. Job hunting is hard.<p>Good luck.