Dr Paul van Loon joined consultancy and data solutions provider Forecast in 2018 and was recently promoted to Director of Data and Analytics.
Paul has extensive experience in machine learning, predictive modelling and data strategy and was previously responsible for advancing the analytical capabilities at Colliers International.
Hamilton Forth’s Atif Hussain recently caught up with Paul to discuss his career to date, his advice for those in the industry, and predictions for the future of data analytics.
What does a typical day look like for you?
I like to get up reasonably early; typically starts with a ‘5’. It allows me some quiet time and means I can get a head start on my day.
After that, my days are pretty varied and any given day will be a mix of looking after the team, meeting with existing and potential clients, recruitment, project reviews, and much more.
Except for myself, everyone in the team is aligned to a project, delivering client-facing work. I merely facilitate the delivery of projects where needed and support the team when I can.
What were your ambitions when you completed your PhD?
After completing my MSc in Applied Statistics and Datamining, I worked as an Econometrician and while I thoroughly enjoyed it, after some time I felt that I was not quite done ‘studying’ yet and needed another academic challenge. When I got the opportunity to pursue my PhD in Actuarial Mathematics, with an involved industry sponsor, I was delighted and decided to go for it.
During my PhD I developed some software that allowed me to join a large global real estate company, perhaps unusually, as they acquired the technology. I’m glad I said yes to the opportunity when it came around.
I don’t think I really had any ambitions other than hoping to find a job and career that would allow me to be continuously challenged, leveraging what I had learned up to that point.
What advice would you give to those looking to pursue a career in data science?
Terminology is so important here and as a field we’ve seen an explosion of roles; not only in number but also in diversity. Decide what kind of ‘data scientist’ you’d like to be in the broadest definition of the term and think carefully about your journey to getting there.
The barrier to entry is relatively low leading to a lot of junior candidates in the market without a real idea of where they fit in. Think about the value you can add, rather than the technologies you have mastered. Build a solid foundation of real-world analytics, rather than a portfolio of copy-paste pet projects on Github.
I think there’s an interesting career path for particular types of ‘software engineers’ to work in Data Science. As the industry continues to move to a world where the ML hype cools off and continued investment is contingent on demonstrable returns, we see Data Science move from ‘building models’ to ‘using models’. The harsh reality of building, using, and maintaining a ML based solution is one of the reasons that all the ‘Ops’ acronyms are so popular right now.
What are your predictions for the evolution of technology within data analytics/data science?
I think the three large cloud platforms (AWS, GCP and Azure) will play an important role in this, continuing to abstract away ‘technological’ and ‘machine learning’ complexities, making the technology available for developers with and without deep understanding of the nuances. The shift towards implementation and value, away from ‘building models’ is reflected in the job market today, with Data Engineers being some of the most sought-after people in the industry.
I also think we will see a normalisation of Data Science in the sense that there will not be a need to advertise that a platform you built “uses AI to do x”, but that we focus on the benefits derived from a product or service, with the assumption that some of the underlying technology will include ‘data science’ to get us there.
What career advice would you give yourself when you were younger if you could?
Are you saying I’m old?
I’d encourage myself to take career risks; they’ll probably pay off.
You want to be the person that says ‘yes’ to things; you’ll struggle, make mistakes and as long as you learn from them, opportunities will come, and people will gravitate to you.
Make sure you’re always out of your comfort zone; your comfort zone will not push you to grow but the team around you will.
When you joined Forecast in Nov 2018 you were tasked with setting up the analytics division which is now a well-established team of 15. Tell us a little bit about this journey.
The journey Forecast has been on as a business has been fascinating for me to be part of. The growth of the Advanced Analytics team (still growing, join us!) plays an important role in the company’s journey.
The journey in maturity and the operating rhythm that goes along with growing from a team of one, to now a full team, is one with many challenges. It’s important to mention that all of our growth is driven by client demand. We have grown one consultant at a time, rather than growth through the injection of capital. In the last twelve months we have spent a lot of time codifying our practices and processes, our vision and values, and people strategy. This solid foundation will help us achieve ambitious growth targets.
If you weren’t working in technology, what other profession do you think you would’ve pursued a career in?
I would never really have noticed that I work in ‘technology’, but I guess I do. While I can get an awful lot of satisfaction around a successful piece of technology, I am genuinely more interested in what those solutions allow us to achieve; trying to solve real-world problems that real-world businesses are dealing with.
I think I probably would have ended up somewhere in some financial institution, still working with numbers and data, but closer to the finance. I’m much more interested in looking ahead than looking back though and with careers much more fluid than ever before, who knows where we will be in ten years.
Tell us a bit about the Advanced Analytics division at Forecast.
The Advanced Analytics division at Forecast was formed in Jan 2019, and we have since grown to a team of 15. Given how we’ve always serviced our clients with a relatively broad range of services when it comes to data science, we pride ourselves on being generalists, a very wide T-shaped experience. As we’ve grown, we see how different roles are being carved out quite naturally, whether this is a pure technical specialisation or an interest in running the business.
I always like to point out how close a team we are, even at 15 people. Everyone in the team will know what project/client anyone is working on and probably even give you the pitch of what we’re trying to do; this awareness is great for the team and winning new business. This is something we are very proud of.
Two dimensions of the diversity spectrum that I particularly love about Forecast is the diversity in previous experience and diversity of nationality. Data science brings together people from all educational and professional backgrounds and our team is a good example of that. Not only does this diversity make for a fun place to work, but it also allows us to serve our clients’ needs better.
If you could invite two people to a dinner party (living or deceased) who you choose and why?
I don’t think I’m interested in getting historical thinkers and explorers to have dinner with me. I’d bring along two individuals that I hugely admire for what they have achieved and how they appear to carry themselves. Just nice guys.
I’d get Roger Federer to come along. Besides his class and elegance when it comes to tennis, the longevity of his career is absolutely insane, and his passion for the game unparalleled. After having achieved everything there is to achieve, he continues to push hard to stay in a position where he can challenge for major titles. I hope he blesses us with another year or two on the courts.
I’d also ask Arnold Schwarzenegger to join us. The hard work and dedication to his bodybuilding career, leveraging his success into a Hollywood career and leveraging his newfound success into a political career; incredible. To me, he’s a testament to vision and determination, but I also think he’ll just have the most amazing stories to tell.
I think these two would make for a very entertaining dinner party!
You have recently been promoted to a new role, Director of Data & Analytics, what does your new role look like and what are your immediate plans?
We’ve recently hired a terrific Head of Data Science to support me and take a lot of ownership over the team. As we have grown, I have naturally absorbed a lot of additional responsibilities and giving some of these away, should afford me the luxury of time to contribute to our ambitious plans for further growth. I’ll continue to focus on looking after our existing clients, meeting with prospective clients as well as provide technical leadership on key projects.
For a confidential discussion about your technology recruitment requirements contact [email protected]
10 Questions with… Dr Paul van Loon, Director of Data and Analytics at Forecast
Dr Paul van Loon joined consultancy and data solutions provider Forecast in 2018 and was recently promoted to Director of Data and Analytics.
Paul has extensive experience in machine learning, predictive modelling and data strategy and was previously responsible for advancing the analytical capabilities at Colliers International.
Hamilton Forth’s Atif Hussain recently caught up with Paul to discuss his career to date, his advice for those in the industry, and predictions for the future of data analytics.
What does a typical day look like for you?
I like to get up reasonably early; typically starts with a ‘5’. It allows me some quiet time and means I can get a head start on my day.
After that, my days are pretty varied and any given day will be a mix of looking after the team, meeting with existing and potential clients, recruitment, project reviews, and much more.
Except for myself, everyone in the team is aligned to a project, delivering client-facing work. I merely facilitate the delivery of projects where needed and support the team when I can.
What were your ambitions when you completed your PhD?
After completing my MSc in Applied Statistics and Datamining, I worked as an Econometrician and while I thoroughly enjoyed it, after some time I felt that I was not quite done ‘studying’ yet and needed another academic challenge. When I got the opportunity to pursue my PhD in Actuarial Mathematics, with an involved industry sponsor, I was delighted and decided to go for it.
During my PhD I developed some software that allowed me to join a large global real estate company, perhaps unusually, as they acquired the technology. I’m glad I said yes to the opportunity when it came around.
I don’t think I really had any ambitions other than hoping to find a job and career that would allow me to be continuously challenged, leveraging what I had learned up to that point.
What advice would you give to those looking to pursue a career in data science?
Terminology is so important here and as a field we’ve seen an explosion of roles; not only in number but also in diversity. Decide what kind of ‘data scientist’ you’d like to be in the broadest definition of the term and think carefully about your journey to getting there.
The barrier to entry is relatively low leading to a lot of junior candidates in the market without a real idea of where they fit in. Think about the value you can add, rather than the technologies you have mastered. Build a solid foundation of real-world analytics, rather than a portfolio of copy-paste pet projects on Github.
I think there’s an interesting career path for particular types of ‘software engineers’ to work in Data Science. As the industry continues to move to a world where the ML hype cools off and continued investment is contingent on demonstrable returns, we see Data Science move from ‘building models’ to ‘using models’. The harsh reality of building, using, and maintaining a ML based solution is one of the reasons that all the ‘Ops’ acronyms are so popular right now.
What are your predictions for the evolution of technology within data analytics/data science?
I think the three large cloud platforms (AWS, GCP and Azure) will play an important role in this, continuing to abstract away ‘technological’ and ‘machine learning’ complexities, making the technology available for developers with and without deep understanding of the nuances. The shift towards implementation and value, away from ‘building models’ is reflected in the job market today, with Data Engineers being some of the most sought-after people in the industry.
I also think we will see a normalisation of Data Science in the sense that there will not be a need to advertise that a platform you built “uses AI to do x”, but that we focus on the benefits derived from a product or service, with the assumption that some of the underlying technology will include ‘data science’ to get us there.
What career advice would you give yourself when you were younger if you could?
Are you saying I’m old?
I’d encourage myself to take career risks; they’ll probably pay off.
You want to be the person that says ‘yes’ to things; you’ll struggle, make mistakes and as long as you learn from them, opportunities will come, and people will gravitate to you.
Make sure you’re always out of your comfort zone; your comfort zone will not push you to grow but the team around you will.
When you joined Forecast in Nov 2018 you were tasked with setting up the analytics division which is now a well-established team of 15. Tell us a little bit about this journey.
The journey Forecast has been on as a business has been fascinating for me to be part of. The growth of the Advanced Analytics team (still growing, join us!) plays an important role in the company’s journey.
The journey in maturity and the operating rhythm that goes along with growing from a team of one, to now a full team, is one with many challenges. It’s important to mention that all of our growth is driven by client demand. We have grown one consultant at a time, rather than growth through the injection of capital. In the last twelve months we have spent a lot of time codifying our practices and processes, our vision and values, and people strategy. This solid foundation will help us achieve ambitious growth targets.
If you weren’t working in technology, what other profession do you think you would’ve pursued a career in?
I would never really have noticed that I work in ‘technology’, but I guess I do. While I can get an awful lot of satisfaction around a successful piece of technology, I am genuinely more interested in what those solutions allow us to achieve; trying to solve real-world problems that real-world businesses are dealing with.
I think I probably would have ended up somewhere in some financial institution, still working with numbers and data, but closer to the finance. I’m much more interested in looking ahead than looking back though and with careers much more fluid than ever before, who knows where we will be in ten years.
Tell us a bit about the Advanced Analytics division at Forecast.
The Advanced Analytics division at Forecast was formed in Jan 2019, and we have since grown to a team of 15. Given how we’ve always serviced our clients with a relatively broad range of services when it comes to data science, we pride ourselves on being generalists, a very wide T-shaped experience. As we’ve grown, we see how different roles are being carved out quite naturally, whether this is a pure technical specialisation or an interest in running the business.
I always like to point out how close a team we are, even at 15 people. Everyone in the team will know what project/client anyone is working on and probably even give you the pitch of what we’re trying to do; this awareness is great for the team and winning new business. This is something we are very proud of.
Two dimensions of the diversity spectrum that I particularly love about Forecast is the diversity in previous experience and diversity of nationality. Data science brings together people from all educational and professional backgrounds and our team is a good example of that. Not only does this diversity make for a fun place to work, but it also allows us to serve our clients’ needs better.
If you could invite two people to a dinner party (living or deceased) who you choose and why?
I don’t think I’m interested in getting historical thinkers and explorers to have dinner with me. I’d bring along two individuals that I hugely admire for what they have achieved and how they appear to carry themselves. Just nice guys.
I’d get Roger Federer to come along. Besides his class and elegance when it comes to tennis, the longevity of his career is absolutely insane, and his passion for the game unparalleled. After having achieved everything there is to achieve, he continues to push hard to stay in a position where he can challenge for major titles. I hope he blesses us with another year or two on the courts.
I’d also ask Arnold Schwarzenegger to join us. The hard work and dedication to his bodybuilding career, leveraging his success into a Hollywood career and leveraging his newfound success into a political career; incredible. To me, he’s a testament to vision and determination, but I also think he’ll just have the most amazing stories to tell.
I think these two would make for a very entertaining dinner party!
You have recently been promoted to a new role, Director of Data & Analytics, what does your new role look like and what are your immediate plans?
We’ve recently hired a terrific Head of Data Science to support me and take a lot of ownership over the team. As we have grown, I have naturally absorbed a lot of additional responsibilities and giving some of these away, should afford me the luxury of time to contribute to our ambitious plans for further growth. I’ll continue to focus on looking after our existing clients, meeting with prospective clients as well as provide technical leadership on key projects.
For a confidential discussion about your technology recruitment requirements contact [email protected]
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