Have you explored opportunities to apply data science to agriculture?
I'm interested in this space; I do some work with agricultural data acquisition hardware and software (e.g., soil moisture, environmental conditions, sap flow, plant/fruit growth monitoring), irrigation, fertiliser application) and I'm interested in ways this data could be used in predictive models, but I'm not at the stage of being able to focus on that aspect yet (still getting the core data logging/display tech working well, though we’re nearly there).
Feel free to get in touch (email in profile) if you'd like to connect and discuss.
To address your question, I think the world is still mostly at a very basic stage in its use of data analysis and statistics. Most of the talented people are employed on big salaries by a relatively small number large companies with huge budgets for specific applications (e.g., ad targeting, risk assessment, algorithmic trading).
But outside of that, not much is happening, so I think there are big opportunities to apply data science in new fields and make the benefits more widely distributed.
But seriously, if you have a background in agriculture (and don't hate it) and want to get into data science, aim for the intersection of the venn diagram between agriculture and data science.
I understand agriculture is getting quite technical and data driven these days, and that can surely only become more the case in the future. Especially if vertical farms and robot tractors become a real thing.
This. Leverage the strengths you already have —agriculture— to help you get to where you want to get to. In another field, a junior data scientist with an agriculture phd is just a junior data scientist. In your field, you’re either a phd with a strong extra skill in data science, or a junior data scientist with a superpower.
The skill sets most needed for vertical farms probably have nothing to do with agriculture. If that is your goal then you should research or design fusion reactors instead.
It is hard imagine that all those millenia of knowledge about growing crops is going to be irrelevant, even if you manage to take soil, seasons and pests out of the equation.
> Have you explored opportunities to apply data science to agriculture?
This is the most straightforward route imo. Just pick up some of the skills required to get going, which it sounds like they are based on the post, and just start tweaking with stuff in your field. They already have a great advantage of specialized knowledge about the subject they would be applying it to and Ag, from someone who grew up and worked on a row crop farm, seems very ripe for exploration through data science.
I just started getting interested in sensors and ranching/agg. Can you link me any resources? Curious on the right terminology, some players in the space, etc. any help pointing me in the right direction would be really appreciated!
I'm interested in this space; I do some work with agricultural data acquisition hardware and software (e.g., soil moisture, environmental conditions, sap flow, plant/fruit growth monitoring), irrigation, fertiliser application) and I'm interested in ways this data could be used in predictive models, but I'm not at the stage of being able to focus on that aspect yet (still getting the core data logging/display tech working well, though we’re nearly there).
Feel free to get in touch (email in profile) if you'd like to connect and discuss.
To address your question, I think the world is still mostly at a very basic stage in its use of data analysis and statistics. Most of the talented people are employed on big salaries by a relatively small number large companies with huge budgets for specific applications (e.g., ad targeting, risk assessment, algorithmic trading).
But outside of that, not much is happening, so I think there are big opportunities to apply data science in new fields and make the benefits more widely distributed.