Many of the most promising potential routes to solving the hardest biology problems are heavily maths and software dependent. We use high-throughput techniques

Many of the most promising potential routes to solving the hardest biology problems are heavily maths and software dependent. We use high-throughput techniques to generate a lot of data of different types, then use mathematical insights and computational power to reduce the data, then more maths and machine learning to extract meaning. That maths degree probably means, at the least, that you're comfortable learning graph theory, combinatorics, discrete optimisation, probability theory, etc. These things are the foundation of systems and computational biology. The software development skills are also sorely needed - a huge proportion of computational biology software is unusable outside of the lab that developed it, and well-engineered software underpins a LOT of successful research. Many great ideas go wasted due to lack of good programmers to implement them properly. I would say there are two ways in: 1. Stay in your current job, and do hobby work collaborating with scientists to write scientific FOSS and publish it. If you're interested in this, I have a long list of ideas. 2. Transition to science - get a job in a bio lab or at a computational biology/genomics institute. Depending on the specific problem you want to work on and where in the world you are, I can suggest places. Probably 1, then 2 would be a good idea.