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Russell knew he didn’t want to stay in academia, but wasn’t sure what to do next. A tip from a friend pointed him toward data science—and a few courses on Coursera helped him land his first industry job, which eventually grew into a leadership role with a major company. Here’s his story:
If you had told me two years ago that I would be head of data science for the UK’s largest retail casino operator, I would have said you were crazy. And yet, that’s exactly what happened.
In 2015, I was working as a postdoctoral researcher at the University of the Western Cape in South Africa. I’d been in the same role for 6 years, since finishing my Phd in astronomy in 2009, and I was beginning to question my future in research—I knew it would be difficult to transition from a postdoc to a tenure-track position, and I now had a family to support.
I started thinking about alternative career paths, but I couldn’t see an obvious industry to switch to that wouldn’t require me to undergo extensive re-training. Then a colleague suggested I look into data science. I did a bit of research, and realized that this was a rapidly-growing industry that actually did require many of the same skills I’d been using in my academic research.
When I began looking into fellowship programs aimed at helping research scientists transition to data science, a number of the people I spoke to pointed me toward Coursera and Andrew Ng’s Machine Learning course. I enrolled, and found the course to be a great introduction—it was very hands-on, and I felt like I was gaining insight into the nuts and bolts of various machine learning approaches, rather than just treating them as a black box.
After completing Machine Learning, I was hungry for more. I started the John Hopkins Data Science Specialization, which proved to be a very good introduction to working with real-world industry data. I became more and more confident in my new direction, and decided to leave my postdoc role to move back to Scotland, where I began interviewing for various data science roles. Eventually, I landed a job as a data science manager with Rank Group, which owns Grosvenor Casinos.
Since then, I’ve settled into working with the amazing team here and tackling several fascinating projects, including building propensity models to predict when a customer is going to lapse, identifying potential VIPs based on their first visit in casino, and developing predictive models to detect potential problem gamblers (I feel fortunate to work with a company that takes responsible gambling very seriously). I’ve seen my role expand to head of data science for Grosvenor Casinos (retail). And I haven’t forgotten my academic roots—I’ve successfully advocated to start a summer intern program, through which we’ll be giving students the opportunity to get their hands dirty and learn some on-the-job data science.
The post From astronomy postdoc to retail data scientist appeared first on Coursera Blog.
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If you had told me two years ago that I would be head of data science for the UK’s largest retail casino operator, I would have said you were crazy. And yet, that’s exactly what happened.
In 2015, I was working as a postdoctoral researcher at the University of the Western Cape in South Africa. I’d been in the same role for 6 years, since finishing my Phd in astronomy in 2009, and I was beginning to question my future in research—I knew it would be difficult to transition from a postdoc to a tenure-track position, and I now had a family to support.
I started thinking about alternative career paths, but I couldn’t see an obvious industry to switch to that wouldn’t require me to undergo extensive re-training. Then a colleague suggested I look into data science. I did a bit of research, and realized that this was a rapidly-growing industry that actually did require many of the same skills I’d been using in my academic research.
When I began looking into fellowship programs aimed at helping research scientists transition to data science, a number of the people I spoke to pointed me toward Coursera and Andrew Ng’s Machine Learning course. I enrolled, and found the course to be a great introduction—it was very hands-on, and I felt like I was gaining insight into the nuts and bolts of various machine learning approaches, rather than just treating them as a black box.
After completing Machine Learning, I was hungry for more. I started the John Hopkins Data Science Specialization, which proved to be a very good introduction to working with real-world industry data. I became more and more confident in my new direction, and decided to leave my postdoc role to move back to Scotland, where I began interviewing for various data science roles. Eventually, I landed a job as a data science manager with Rank Group, which owns Grosvenor Casinos.
Since then, I’ve settled into working with the amazing team here and tackling several fascinating projects, including building propensity models to predict when a customer is going to lapse, identifying potential VIPs based on their first visit in casino, and developing predictive models to detect potential problem gamblers (I feel fortunate to work with a company that takes responsible gambling very seriously). I’ve seen my role expand to head of data science for Grosvenor Casinos (retail). And I haven’t forgotten my academic roots—I’ve successfully advocated to start a summer intern program, through which we’ll be giving students the opportunity to get their hands dirty and learn some on-the-job data science.
The post From astronomy postdoc to retail data scientist appeared first on Coursera Blog.
Continue reading...
