You did all the right things:
- getting a quantitative degree from a good university,
- or doing some internship,
- attending a few online classes (Coursera),
- spent a few weeks on a valuable data science boot camp or our data science apprenticeship, working on real big data – especially automating data processes – even gained a certification (ours is cost-free, no exam required; it is based on your accomplishments),
- followed these guidelines,
- read data science job interview questions,
- and read a few books (including ours which provide innovative, outside-of-the-box, modern content)
Now you are wondering, how do I reap the benefits? Here are five unusual ways to land a data science job: without having a resume, and without ever checking a single job ad. And once on the job, read 5 ways a data scientist can get fired.
- Attend conferences, events or webinars. Talk to conference speakers: ask pertinent questions (not job related) and provide feedback about their talk. Even better: get invited as a speaker. Conference organizers are desperate to find quality speakers.
- You can also create and organize some local events yourself, using Meetup. It’s cheap and easy.
- Publish. A book, an article, a chapter for an author (as long as your name is mentioned). Even better and easier: post blogs on community websites such as DSC, or with a traditional tech publisher. On DSC, you don’t need to have experience writing blogs – all quality submissions are accepted, and you will reach the largest audience of analytics practitioners – many of them are also hiring managers, some are recruiters.
- Work hard on your LinkedIn profile: ask colleagues for endorsements, mention awards, list articles, projects and presentations (Slideshare), write articles on LinkedIn Pulse, mention success stories on your profile. Add your skill list (see picture below).
- Develop an interesting API, web or mobile app, and hope that it will be downloaded, or used by at least a few hundred people (it will sure get boosted if you talk about it on DSC). For instance, our intern developed a web app (API) that allows you to track the top data scientists to follow on Twitter, using AWS and Python, and later found a full time job in New York City. Another data scientist created an app that makes it very easy, with nice formatting, to navigate DSC on a mobile phone.
Add your skill list on LinkedIn, have your colleagues / boss / clients endorse it (and reciprocate!)
If in the short term you don’t need money, you can also contact employers and offer to pay them to be accepted to work for them (in short, your hourly rate is negative). This makes sense only if you are looking to gain some specific experience (or work on specific data) that is hard to get outside the job in question. You are likely to experience a high rejection rate thought, worse than if asking a salary significantly above market rate. Another idea is to work remotely for overseas employers. Finally, there are ways to make money, as a data scientist, without working for an employer or a client. For instance, harvesting, summarizing and selling data or reports.
DSC Resources
- Career: Training | Books | Cheat Sheet | Apprenticeship | Certification | Salary Surveys | Jobs
- Knowledge: Research | Competitions | Webinars | Our Book | Members Only | Search DSC
- Buzz: Business News | Announcements | Events | RSS Feeds
- Misc: Top Links | Code Snippets | External Resources | Best Blogs | Subscribe | For Bloggers
Additional Reading
- What statisticians think about data scientists
- Data Science Compared to 16 Analytic Disciplines
- 10 types of data scientists
- 91 job interview questions for data scientists
- 50 Questions to Test True Data Science Knowledge
- 24 Uses of Statistical Modeling
- 21 data science systems used by Amazon to operate its business
- Top 20 Big Data Experts to Follow (Includes Scoring Algorithm)
- 5 Data Science Leaders Share their Predictions for 2016 and Beyond
- 50 Articles about Hadoop and Related Topics
- 10 Modern Statistical Concepts Discovered by Data Scientists
- Top data science keywords on DSC
- 4 easy steps to becoming a data scientist
- 22 tips for better data science
- How to detect spurious correlations, and how to find the real ones
- 17 short tutorials all data scientists should read (and practice)
- High versus low-level data science
Follow us on Twitter: @DataScienceCtrl | @AnalyticBridge