Hedge funds could look very different in a few years.
The Financial Times published an article about the rise of DIY algorithmic traders – people who develop automated investment strategies.
These people don’t work for hedge funds or banks on Wall Street.
Instead, they are mathematicians, progammers, physicists and data experts who are using their skills and cheap, powerful computers to tackel investing.
And this is happening everywhere we look.
Online sales are hyper-competitive, and the companies with an algorithmic edge can squeeze out more profits from their platforms.
Recommendation engines are key to keeping users interested, as algorithms work out personalised offers.
The energy business is fuelled by data – from meters recording generation output to those working out who has consumed it and what their bill should be.
In a world of abundant, cheap money, projects have to work on razor thin margins.
Getting the numbers wrong, over time, will mean that the project makes negative returns.
So, who is going to succeed in this new world?
Drew Conway came up with the Data Science Venn Diagram to explore the key skills needed in the world of Data Science – the field that will most likely underpin modern work.
In adapted form, the key is having three sets of skills.
Hacking skills are an entry requirement – being able to deal with and clean text and numeric data is part of every project.
Excel won’t hack it anymore – we’re going to have to use better tools to deal with more and messier data.
Then we need some maths and stats knowledge.
Knowing how to draw and interpret charts and understand the relationships between sets of numbers makes the difference between guessing and having a theory.
And a scientific approach is based on having hypotheses and running experiments.
Finally – many people think they can simply waltz into a new field and take it over.
Domain knowledge often makes the difference between success and failure in a field – it’s very hard for someone to build a tool to solve a problem that they have never experienced themselves.
That’s why we get lots of tools that look pretty, but end up doing little.
Curious people with good tools are what we need for modern work.