Maybe this is a weird question for Operations Research SE, but I seek to get paid for my operations research skills while working remotely. I already have accounts on freelancing websites. However, I exert a lot of effort in refusing to do students' homework. Would anyone please suggest another way?
For me, the three necessary ingredients to get (O.R.) consulting work usually are:
The potential client has to
- Know me
- Like me (personally, as well as being confident I will do a good job)
- Have money (which they are authorized to spend on a consultant)
It's not so easy to find all three together.
There are many people who know me. Of those who know me, a significant portion (but much less than 100%, ha ha) like me.
At any given time, of those who know me and like me, only a very small portion have money (which they are authorized to spend on a consultant). However, "having money" is a stochastic process, so some who know me and like me, but don't have money now, may have money later.
There are some who know me and have money, but don't like me. Usually, it's not easy to convert someone who dislikes you to like you. But it can happen, especially if the reason for their dislike was not based on first hand knowledge, so their dislike may not be very strong or immutable.
Of course, when you do get work, you better deliver the goods, or the liking will very soon turn into strong disliking. I am not a practitioner of "fake it til you make it". Some people are. I turn down potential gigs which I don't think will work out well, and which would leave the client dissatisfied. Better to disappoint them by not taking the gig, than to take the gig and disappoint them with unsatisfactory outcome.
However, I am open to expanding my horizons. If I do some unpaid looking into/figuring out things before agreeing to a new gig for which I didn't have all the needed skills, and convince myself I can do it, I will take the gig. I do not consider that to be faking it til I make it, because I will have already made it before taking it, so there's no faking it.
It is easy to start a business/become a consultant. Getting (profitable) revenue is the hard part. There are quite a few people on LinkedIn with impressive resumes, who after retiring or being downsized from a company, become consultants, sometimes with an impressive sounding company name. Their LinkedIn consulting entry has several lines of very impressive sounding capabilities and the kind of (often high level executive) clients they serve, often written in an active voice, as though they have actually done these things for these clients. In many cases, after one or two years, they have yet to get any paying clients.
I had been doing some freelance jobs through platforms like Upwork and Guru, but there are not so many job postings about OR (and, in several ones, hourly rates are not so high, too). Most of the jobs are disguised in machine learning or data science job postings. And also, they are usually not pure OR jobs, but small apps or libraries that solve an OR-related problem (ie, usually not AMPL-related jobs, for example).
So, if you want to monetize OR as a freelance, learn how to code and develop small apps. And learn something about machine learning and data science too.
Said that, I totally agree with @fontanf comment. You have to build a strong network, so use these sites in order to build that and get some experience. They could also be an entry point for bigger projects.
Concur with above replies and comments.
Also, in the industry OR apps are pretty complex. The number of constraints will be mind-boggling and often difficult to formulate if you don't have some domain knowledge. That's why in the industry OR is implemented by a team. That also explains why some ML/DS projects keep failing if domain experts are not working together.
Also freelancing sites like taproot may offer some interesting projects but there could be others who may seek help because they are stuck in a part of their project. Apart from communications, suddenly being pulled into middle of a project you may not get the head and tail of it. It happens on this stackexchange site sometimes. Users will post either from a book or paper or part of industry work with some unclear concept or error in print and then you have to wonder.
Still regularly visit or.stackexchange or equivalent stats and math site. While stats and math sites will be purely PhD level stuff, OR subsite does have content that clarifies concepts. These may be handy in the industry or during interviews.
Disclaimer: I do myself browse Taproot and Upwork myself and agree getting an OR project is difficult. Most are ML/DS ones with may be a new optimization trick.