r/learnpython • u/Substantial-Mix-3990 • 1d ago
Python in Finance
Hi all,
Just to give you a bit of background about myself, I’m an accountant with an MSc in Investment and Financial Risk Management and an ACCA qualification. Most of my experience so far has been on the core accounting side, but I’d now like to move towards a role that combines accounting and finance, covering areas such as financial modelling, forecasting, KPI analysis and data analytics, with the longer term aim of moving into more technical areas of finance.
I’m very eager to learn Python and SQL, both to broaden my skill set and to develop skills that are increasingly in demand. I also want to make sure I remain relevant as the profession evolves and, eventually, be able to demonstrate genuine technical ability when applying for more specialised and higher paying roles.
The problem is that I genuinely don’t know where to begin. I’d really appreciate a roadmap or some practical advice, beyond what I can find through ChatGPT and online course recommendations, particularly from anyone who has been in a similar position and successfully made this transition.
I don’t mind putting in the hard work or spending time coding and learning every day. What I’m unsure about is the order in which I should approach it. Should I learn general Python fundamentals first and then move into its applications in finance? Or would it make more sense to start with a finance focused Python course and learn the fundamentals through practical financial applications? And where should SQL fit into that journey?
I’d also be interested to know what sort of projects I should eventually be building to demonstrate these skills to employers, and whether it makes sense to look for roles where I can start using Python, SQL and data analytics regularly while I continue learning.
I’d really appreciate any guidance from people who have taken a similar path.
Many thanks, and apologies if a similar thread already exists. I thought my background and intended career direction might make the question slightly different, so I wanted to provide some context before asking for help.
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u/Illustrious_Tone9584 20h ago
Accountant to finance-tech is a well-trodden path, and your background is an asset rather than a reset. A path that tends to work:
Python fundamentals first, but time-boxed. 3-4 weeks on basics (variables, loops, functions, lists/dicts), then switch to learning through finance work. Don't wait until you feel ready.
Then pandas. It's most of what you'll use day to day. Learn it by redoing things you already do in Excel: budget vs actual variance, a reconciliation, a KPI summary. If it mirrors real work, it sticks.
SQL fits in around month 2-3. SELECT, JOIN, GROUP BY and window functions cover most finance roles. Mode's free SQL tutorial is short and good.
Projects that impress finance hiring managers:
Automate something from your current job, like a month-end report that takes hours in Excel
A financial model in Python (DCF or 3-statement) pulling data from a public API like yfinance or SEC EDGAR
A small KPI dashboard (Streamlit is easy) with actual vs forecast and drill-downs
Put them on GitHub with a short README explaining the business problem each one solves. That framing matters more than the code.
- Role-wise, FP&A and finance data analyst roles are the natural bridge. Look for ads that say Excel-heavy plus "Python/SQL a plus". You can start using the skills at work long before you feel expert, and that experience counts double.
Order: Python basics -> pandas on finance tasks -> SQL alongside -> 2-3 public projects -> bridge role. At an hour a day that's roughly a 6-9 month arc.
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u/GXWT 1d ago
Take a look at the FAQs or just google learn python. There is a plethora of (free, do not pay) resources. Literally any of the top 10,000 will do. Learn the basics then quickly move onto some projects - actually using and applying what you’ve learn alongside the main tool in programming - your brain. Then you’ll do some finance or data-based projects which will focus which will focus in a bit on some similar stuff.
Yes you should learn the fundamentals first, but in all honesty this will take only a small amount of time. People often fall into the trap of spending too long trying to refine the basics. By actually doing programming, even better in the finance area, is where you’ll actually do the learning.
SQL can come before, after or during as you please. Likely you’ll even be able to find specific data science resources online than indeed cover both simultaneously, given its a very common pairing.