I'm in a unique situation so please bear with me while I provide a little background. I'm 33 and I've never been under employment. I was always a high achiever at school but I never had any dreams or any goals, and my only real talent was "being good at school". I graduated with a first in Physics(bsc) from a top uni which is (or was) obviously huge, but then I kinda took my foot off the gas and allowed myself to meander. I got really into poker which was very easy money at the time. As someone who never had money before and had no real dream to follow this was very attractive, and I ended up dropping out of my masters to play full time. Naively I thought this was my key to riches and happiness, but this was around the time where Poker died in the US and games got exponentially harder. A few years later and I discovered I was nowhere near as good as I thought, so I started up an online jewellery business. This went extremely well for a few years but as with most good things the honeymoon phase didn't last. I still make a reasonable amount of money for my frugal lifestyle and I own a house, but I'm constantly haunted by the feeling of underachieving. I want to put my degree to use because I know I'm a smart person who should be doing something I'm proud of, but I really have no idea what. I've applied for basic, minimum wage jobs just to get some experience and some variety, but so far I have always been turned down because I'm just "not the right fit". If I'm really committed to a new career path at this point in life, what do you think my best course of action is? I have a very good degree, but old and unused. No employment history. Proof that I have run a successful self employed business. I'm open to more studying, but I'mnot interested in becoming a hardcore academic - I just don't think I'm smart enough for that anymore. Is there anything I may not have thought of where my history would give me a head start, or should I accept that I need to start from square one?

Any interest in Data Analytics / Data Science? Maybe learn SQL / Python to help with it and do some online training and you should then be able to look for some entry level roles?

Software dev. Stock answer if the asker seems fairly alert. Write some code, if you enjoy it, show some prospective employer said code.

Eh? Why do that? I mean if your business provides an income for you at the moment then what is the point in some min wage job? If anything it would ruin the potential narrative on your CV IMO. Do an MSc, if you've got a 1st from a top uni then you're going to have a reasonable shot at various programs. You'd be able to make use of the uni careers service and you'd be a recent grad as far as employers are concerned. You've also got a story to tell re: your past on your CV - professional poker player then set up own company... that's fine/can be explained - don't go and trash that story by then getting some random min wage job - currently you're an established business owner looking for a career change. Why not look at doing something combining maths/computing etc... if you're not going for academia then a straight physics MSc might not be so useful though various physics departments offer Scientific Computing MSc degrees - mixture of numerical methods, programming, high performance computing etc... that's pretty useful for various companies. If you have some elective modules you could also throw in some mathematical finance or stats/ML modules. Or indeed an MSc in either of those areas could be useful too.

Thanks, some good suggestions here. I think if I'm going to have a proper shot at a career change then I'll either need a fresh MSC or train as a teacher. I love the idea of being a teacher but honestly I'm not sure I have the required level of charisma. MSc in Data Science or Comp Science would be a safe bet. Robotics / Machine learning stuff peaks my interest a little more though. I have no coding experience so Software dev stuff seems far fetched. I live close to Bath / Bristol so I have pretty good options in terms of courses. Moving isn't an option right now as I have the house and elderly pets. Maybe online only course is worth looking at since I'm not well off enough that I can completely neglect my business while I study. Some stuff to think about for sure. If not for this year then the next.

Don't bother with a general computer science degree if you're looking for more of a data science career you'd be better off with a Stats MSc than a (general) computer science MSc with a couple of ML electives. Plenty of stats MSc courses will include some ML anyway and plenty of ML overlaps with stats in the first place. Also don't worry too much about programming at least for the purpose of completing an MSc - it's mostly R, Matlab and/or Python(Numpy etc..) you'd be using which if you're thinking in terms of linear algebra and generally avoiding using loops is all pretty intuitive. In terms of online courses Imperial has recently launched an online Machine Learning and Data Science MSc, UC Dublin has an online MSc in Data Analytics (which looks to be basically a rebranded MSc in Statistics) and Sheffield has a distance learning MSc in Statistics too, albeit you would seem to need to attend in person for exams and an induction period. Your best bet is probably the new Imperial course - it would be worth demonstrating some interest by having a go at some kaggle competitions, maybe doing some ML related MOOCs and picking up a bit of python while you're at it. (also well worth familiarising yourself with R too) - in some fields you might find that there are some useful R libraries which you might want to make use of/call from python say. Also if you're coming from a Physics background then you've probably got the multivariate calculus and basic linear algebra sorted (though worth reviewing if it has been a few years) - there are some mathematics for machine learning courses on coursera provided by Imperial which could serve as revision, also the multivariate calc and linear algebra courses on MIT open courseware. Though assuming you're up to speed on the more basic undergrad applied maths then for additional maths background this course would be useful: https://ocw.mit.edu/courses/mathema...-processing-and-machine-learning-spring-2018/ Also this book: https://www.amazon.co.uk/Numerical-Linear-Algebra-Lloyd-Trefethen/dp/0898713617 And Boyd's courses on the SEE site: https://see.stanford.edu/Course/EE263 https://see.stanford.edu/Course/EE364A https://see.stanford.edu/Course/EE364B would also be worth getting up to speed on undergrad stats too to get to the same level as maths/stats undergrads - get yourself a statistical inference book aimed at 3rd year undergraduates - for example Casella and Berger: https://www.amazon.co.uk/Statistical-Inference-Casella-George/dp/8131503941 or indeed Wasserman's "All of Statistics" - which is quite a neat book and perhaps a bit broader in terms of coverage. do the above in the year before you plan to start the course and you'd be well prepared... of course you could also look at completing an introductory ML MOOC - like Andrew Ng's on coursera (this uses Matlab/Octave), or the statistical learning one on Stanford online (this uses R) or the Caltech one (this latter one perhaps more useful if you're going to be formally studying this stuff as it is a bit more rigorous) - likewise worth looking at some of the deep learning courses too and getting to grips with PyTorch or Tensorflow in addition to getting used to NumPy and SciKit Learn. Some of the popular text books are freely available online if you want to get a head start - for example: https://web.stanford.edu/~hastie/ElemStatLearn/ http://www.inference.org.uk/mackay/itila/book.html http://web4.cs.ucl.ac.uk/staff/D.Barber/pmwiki/pmwiki.php?n=Brml.HomePage and for DL specifically: https://www.deeplearningbook.org/ and for RL specifically: http://www.incompleteideas.net/book/the-book-2nd.html And for Gaussian processes: http://www.gaussianprocess.org/gpml/ For Bishop and Murphy you'll need to buy the books... and tbh.. you should probably buy any of the above you find useful too if you're going to be using them regularly.

Lastly - this guy's YouTube channel is great: https://www.youtube.com/user/mathematicalmonk/playlists

Given your poker background what about sports betting exchange trading? If you played professional poker for any amount of time you will likely have the skills that cause most people to fail - bank management, discipline etc.