Here some off-the-beaten-path options to consider, when looking for a first job, a new job or extra income by leveraging your machine learning experience. Many were offers that came to my mailbox at some point in the last 10 years, mostly from people looking at my LinkedIn profile. Thus the importance of growing your network and visibility, write blogs, and show to the world some of your portfolio and accomplishments (code that you posted on GitHub, etc.) If you do it right, after a while, you will never have to apply for a job ever again: hiring managers and other opportunities will come to you, rather than the other way around.
1. For beginners
Participating in Kaggle and other competitions. Being a teacher for one of the many online teaching companies or data camps, such as Coursera. Writing, self-publishing, and selling your own books: an example is Jason Brownlee (see here) who found his niche by selling tutorials explaining data science in simple words, to software engineers. I am moving in the same direction as well, see here. Another option is to develop an API, for instance to offer trading signals (buy / sell) to investors, who pay a fee to subscribe to your service – one thing I did in the past and it earned me a little bit of income, more than I had expected. I also created a website where recruiters can post data science job ads for a fee: it still exists (see here) thought it was acquired; you need to aggregate jobs from multiple websites, build a large mailing list of data scientists, and charge a fee only for featured jobs. Many of these ideas require that you promote your services for free, using social media: this is the hard part. A starting point is to create and grow your own groups on social networks. All this can be one while having a full-time job at the same time.
You can also become a contributor/writer for various news outlets, though initially you may have to do it for free. But as you gain experience and notoriety, it can become a full time, lucrative job. And finally, raising money with a partner to start your own company.
2. For mid-career and seasoned professionals
You can offer consulting services, especially to your former employers to begin with. Here are some unusual opportunities I was offered. I did not accept all of them, but I was still able to maintain a full time job while getting decent side income.
- Expert witness – get paid by big law firms to show up in court and help them win big money for their clients (and for themselves, and you along the way.) Or you can work for a company specializing in statistical litigation, such as this one.
- Become a part-time, independent recruiter. Some machine learning recruiters are former machine learning experts. You can still keep your full-time job.
- Get involved in patent reviews (pertaining to machine learning problems that you know very well.)
- Help Venture Capital companies do their due diligence on startups they could potentially fund, or help them find new startups worthy to invest in. The last VC firm that contacted me offered $1,000 per report, each requiring 2-3 hours of work.
- I was once contacted to be the data scientist for an Indian Tribe. Other unusual job offers came from the adult industry (fighting advertising fraud on their websites, they needed an expert) and even working for the casino industry. I eventually created my own very unique lottery system, see here. I plan to either sell the intellectual property or work with some existing lottery companies (governments or casinos) to make it happen and monetize it. If you own some IP (intellectual property) think about monetizing it if you can.
There are of course plenty of other opportunities, such as working for a consulting firm or governments to uncover tax fraudsters via data mining techniques, just to give an example. Another idea is to obtain a realtor certification if you own properties, to save a lot of money by selling yourself without using a third party. And use your analytic acumen to buy cheap and sell high at the right times. And working from home in (say) Nevada, for an employer in the Bay Area, can also save you a lot of money.
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About the author: Vincent Granville is a data science pioneer, mathematician, book author (Wiley), patent owner, former post-doc at Cambridge University, former VC-funded executive, with 20+ years of corporate experience including CNET, NBC, Visa, Wells Fargo, Microsoft, eBay. Vincent is also self-publisher at DataShaping.com, and founded and co-founded a few start-ups, including one with a successful exit (Data Science Central acquired by Tech Target). You can access Vincent’s articles and books, here.