The usernames of all 26m reddit accounts that have commented since Dec. 2017. The return on time for Kaggle is not worthwhile if you're after recognition.

At your current job, start trying to find extra things to do that relate to data science and grow from there. It doesn't mean the people who have those are any better at "data science" than you, just that they have been through more training and their group has a higher mean accomplishment in the field. Learn data manipulation in R using base and dplyr functions in this extensive article using financial data. But don't feel obligated to do Kaggle just as a job hunt checkbox.Find the overlap between "companies you want to work for" and "companies which will benefit from hiring you. I wouldn't suggest forcing your first job towards this field to be an actual data scientists instead maybe figure out how to get to a data developer role then perhaps pivot that to a data analyst role then to data science.My path (with no degree) was: Several years as a software engineer -> Analytics, split testing and data analysis at a company (where I started as an engineer) -> a data science in the role of product optimization specialist- Split testing, insight discovery (using map reduce), experiment design, statistical testing.It took me about 1-2 years to pivot from engineer to a data science role. I'd say this is different in kind not just magnitude from someone like the OP who " just completed a few tutorials on analyzing the Kaggle Titanic dataset using R and Python from various websites." Learn how to merge two data frames in R using different types of join.

The biggest advantage is that you can meet the Top data scientists in the world through Kaggle forums. Place it in ~/.kaggle/kaggle.json or C:\Users\User\.kaggle\kggle.json. It could be just a tweaked or augmented version of an existing extension.

Here are some extensions people use today as an example: Similar philosophy applies to Kaggle. Find a local tech company or a co-working space interested in hosting the event for free. It sounds like you're looking for a shortcut, but there really isn't much of one since you have zero experience in a fairly competitive field.How do you apply for a job with zero experience in data science? Honestly though, cool read.New comments cannot be posted and votes cannot be castPress J to jump to the feed. Good luck! I have several top finishes as a result of A LOT of time spent and while it looks nice on my resume, if my only goal was just to get a job then I'd be better off spending all that time applying to more jobs.Kaggle isn't too useful on your resume unless you finish noticeably on a reputable competition and accomplishing that is EXTREMELY time-consuming unless you're a world-class genius who would not have any trouble getting a job in the first place. If time, then honestly no. You will learn and get experience, it will be fun, and it will help potential employers gauge your ability.Kaggle is great but I've never found it useful for jobs. Press question mark to learn the rest of the keyboard shortcuts They're a poor signal of whether a company will be interested in hiring you. My guess is that Python would be an easy transition from your Ruby background (and Python is awesome for scientific computing).Get involved in a community! If you have no experience, you should look into going to graduate school and getting experience. Particularly if those ads are coming strictly from job search sites.Similarly, something like 99.5% of solicitations on social networking sites (LinkedIn, Kaggle) are going to be from recruiters, who likely lack any meaningful understanding of your skills or the position, and who are looking for candidates to submit to job ads.Being able to point to previous work is helpful, and publicizing the previous work you've done can help bring in leads.Here is a frank question (not being rude here): WHY do you want to do "data science"?The answer to that question will definitely determine how you take your next steps. Here’s the Kaggle catch, these competitions not only make you think out …

My job is technically Research Engineer, but I spend every day bouncing between statistics, machine learning, DSP, high performance computing, software testing, hardware testing, algorithm development, and business development. You could also ask for a student (or job-searcher's) discount (you could get up to 50% off).If you're already a bit of a programmer, I would highly recommend There may still be good tech-related meetups in your area, and I would definitely try to check that out.And if there is no data-related meetup in your area it's a good opportunity to start organizing one. Remember, you're not necessarily committing to be a long-term Kaggler.

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