I want to go back into tech. Assuming I want to be a software developer again:
1. What should I focus on learning to get a backend developer job that pays 180k+ in a major market (NY, LA, or SF)? Things I was starting to find interesting towards the end of the main part of my career include scripting to automate build processes, integration tests, and I guess what one could call crude architectural stuff that probably isn't worth the name (Should I build the data layer using a "repository manager" class for each table and inheritance? At what point is it not over-engineering to bring in a cache?).
Trying to enumerate those examples brought home that I did not do anything remotely sophisticated during my career lol :( Maybe if I don't know the answers to basic questions like that, those are the places to start.
Anyways, what are some of the next big things? One thing I think I might like is natural language processing, maybe I should start there.
2. Suppose I want to throw money at this (since I have some now)--is that even possible? For example, any recommendations for coding interview tutoring (which would be something to do near the end of the transition, after several months or more of self-learning)? I was pretty bad at dev interviews the last time I did them several years ago.
Please note:
Why I went into law in the first place and why I want to jump back into tech is not really something I want to hash out in this thread. Suffice to say, my interest in leaving is not because biglaw is awful or high-pressure or the people are toxic or anything like that, as some might think. I basically got very lucky: I am at one of the best firms in biglaw in terms of work-life balance and cordiality. It's certainly the only one I know of that's like this. My reasons for wanting to go back into tech have more to do with things that I miss about tech and business, such as the creative aspect of working on a product, the mission-orientation, etc. I know some of you will say "reflect on why you stopped wanting to be a dev in the first place", but please suspend that argument for purposes of this thread.
Let's assume for now that my timeline for leaving biglaw is probably about a year hence.
Thanks for all advice in advance.
2. While you are earning good money in your biglaw job you should stay there while scoping out a startup you can use your legal quals + programming chops at. Or start your own. If I was starting a legal-falvoured startup and looking for devs I would hire you in a flash and train you to use my stack. Impossible the other way around.
Good luck
Focus on Python, especially if you're interested in NLP.
If you want to get back up to speed quickly, consider a bootcamp (~2 months F/T, ~6 months P/T). There are programs focused on data science. Bonus if you can convince your firm to pay for it.
Leverage your background to position yourself as a consultant. There's lots of demand for basic data analytics tooling in the enterprise space, for example. Once you have a few projects under your belt, it shouldn't be hard to lateral.
Don't waste your time with "legal tech" unless you'd rather spend more time arguing with tech-averse lawyers than coding. There's a lot more opportunity and a lot less frustration in the general market.
Lots of technology innovation going on in this space
>1. What should I focus on learning to get a backend developer job that pays 180k+ in a major market
You could make more as a developer; you could make more as a lawyer, but you're a develawyer (or a lawyeroper) and a non-linearity should apply.
I have some ideas for your profile. First, the obvious ones:
https://www.avodocs.com (YC) does legal documents for startups. You could work one the programing and the legal aspects for the crowd you seem predisposed to serve given your presence in this forum.
https://rebase.co. Description :
>Rebase is a new, safe, and easy-to-use platform by Nomad List for becoming a legal and fiscal resident in countries that want to attract remote workers
It sits between users and lawyers to manage the full process. It started this year and I think you could link up with https://twitter.com/levelsio and see what you could do to scale it.
Again, whether you wear your developer hat and lawyer glasses, or your lawyer hat and developer glasses; the results will be interesting.
Now for the less "obvious" things. I work at a boutique consultancy that builds end to end machine learning products for large organizations. Machine learning means we work with data and working with data means a whole lot of questions that have to be answered. Compliance with a law that was just passed or a legislation project that may become law in the future.
Sometimes, you work with an organization that serves clients, and these clients have data of their clients. The project means you may have to use data of your client A, which is data of their clients B, C, D, which itself is data of the nested "clients" E, F, G.
The conversation becomes: whose data is this ? What can you do ? What can't you do ? What should the client transmit ? Everything ? Out of the question. Is the client very sensitive (health, defense, finance, communication)? Where will the models be trained and what's the data flow (these are the meetings where people talk about territory, sovereignty, and borders). Where will the software be deployed. Which cloud provider, in which country. On-premises ? How to maintain and who will access from where ?
There are many people involved. Many conversations. Many consultations. Mutual availability. Meetings scheduled weeks or months in advance.
How about you productize this for these problems that pretty much every organization that wants to do anything with data has meetings about. No need to re-invent the wheel. You make a cookie-cutter.
One way to do this is to join a large company that does this kind of projects for organizations. Learn what the friction points are, then develop a product (software + legal) to do that.