How would one go about meaningfully contributing to solving problems in genetics without having done the work leading to a MD or PhD (or both)?
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Researchers in our institute were amazed how easy it is to use e.g. google forms to gather data in a reasonable format. Once you get data in a reasonable format you can help them with transforming it/joining it with other sources/cleaning them up. ETLs and data integration are often completely foreign concepts to them.
And that's researchers, you might still start calling them quite computer-competent after you talk to the people in the clinic. All the research is for nothing if it's not brought to "bedside" to benefit the patients in a clinical setting, outside all trials. For that you need to make sure genomics pipelines are automated and reproducible and only clinically relevant information gets to the oncologists (or other doctors) deciding on treatment. This is still not quite there even in the best places.
I think most of the really world-changing stuff will just be hard work on relatively easy problems. It's hard to get excited about these (compared to the latest neural networks or distributed high performance systems) but they need to get done