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"In Data Science, the highest returns (both monetary and being able to choose an interesting job) will go to those who have a combination of technical mastery, the ability to work well in and/or manage a team, and being able to find Data Science solutions to business problems. Communication – visual, written, and verbal – will be key."
DPhil Oxford graduate, previous Associate Professor of Econonics, founder of a machine learning product development studio, and board member of multiple start-ups, small businesses, and even a VC fund; Neil Rankin's knowledge of how Data Science applies to the world of business, as well as social economics, is both vast and inspiring. He's also a cool dad, and architecture fanatic. Get to know our 2019 Cape Town Data Science teacher below.
Neil Rankin, iXperience 2019 Data Science Head Teacher in Cape Town
I do a lot of work trying to solve labour market ‘failures’ in South Africa. South Africa has the highest rate of youth unemployment in the world – more than half of the people aged 30 and under who want to work can’t find any. I’ve been (and am currently) involved with a number of innovative projects to try and improve this.
I was part of the team which helped design, trial, and then evaluate the ‘Employment Tax Incentive’ - a subsidy to companies which employ young people. The results of the work showed that this has been the most successful post-apartheid labour market intervention. In fact, the president recently renewed it for ten years (I’d like to think at least partly due to the evaluation work I was involved with).
I am currently helping Harambee, an organisation which matches marginalised youth to opportunities in South Africa and Rwanda, with their research and data systems. Harambee is a 2019 Skoll Awardee for its innovative work in this space.
I also do work with leap.ly, a start-up in the graduate recruitment space. Here we’re working on how to build matching algorithms which reduce biases in hiring, which given South Africa’s history, are a systematic feature of South Africa’s labour market.
I like that these are all challenging problems but solving them can really impact people’s lives.
There are many things that stand out: there is so much potential in this space; many people are doing interesting and innovative things; it is constantly evolving; and you can see results. Thoughtfully implemented processes and models can make clear differences to businesses and people’s lives.
I particularly like the R community for its inclusiveness and welcoming nature.
Neil with his two sons – all fans of building things
I think we’re going to see an increase in ‘push button’/’plug-n-play’ machine learning (ML), where software will help pick the ‘best’ ML models and parameters. With this, we’ll see development in the ‘cloud architecture’ (possibly by the same providers like the big tech firms) to allow for processing of more data and ‘bigger’/more sophisticated models.
This will make Data Science both more difficult and easier. More people will be able to engage in Data Science work, but they will not understand some of the issues very well, so we’re likely to see increasing numbers of bias or mis-use.
I also think we’re going to see more fragmentation of the Data Science field, and a number of sub-fields emerge. We’re already seeing this – there are already specialised ML engineers who implement models, data visualisation experts (and dashboard creation specialists), and data science ‘translators’ who manage the interface between the data science team and the rest of the organisation.
The skills that someone requires depends on where they see themselves in the field, but I do think the highest returns (both monetary and being able to choose an interesting job) will go to those who have a combination of technical mastery, the ability to work well in and/or manage a team, and being able to find data science solutions to business problems. Communication – visual, written, and verbal – will be key.
I am hoping that they will come away with exposure to a wide range of Data Science techniques and an ability to implement these. I am also going to focus on how these can be used in a business sense, so that they can have a set of skills which will be valuable if they end up looking for a Data Science job.
Enjoy it and engage with each other, the course, and South Africa, and Cape Town. Many of the issues which South Africa is confronting are present in other societies, perhaps not so explicitly, and thus it is a pretty good bellwether for both issues and solutions.
I love architectural design and how spaces create interactions. One of the highlights of my recent European trip was visiting the Bjarke Ingels designed M/S Maritime Museum of Denmark, as well as seeing the Amager Resource Center (ARC) waste-to-energy plant — the latter which incorporates both a ski slope and climbing wall on the building exterior.
I like books by Haruki Murakami and could reread some of his works like 1Q84, The Wind-Up Bird Chronicle, and Norwegian Wood. The Big Lebowski always makes me laugh, even more now since our elder son calls his brother ‘The Dude’.