We are back with another Behind The Scenes feature, and today we are chatting with Nabeel, our Product Manager from the Singapore office. To find out what a Product Manager does at Parcel Perform, continue reading! You can also check out our other team members by clicking here.
Tell us more about you, who is Nabeel?
I’m Nabeel, I moved from Sydney, Australia to Singapore about 9 months ago. Back in Australia, I enjoyed playing rugby, basketball and spending time at the beach. So far, Singapore has been able to tick two of those three things off. I think I might give rugby a miss in this heat!
I’ve worked in a range of roles over the past seven years – from accounting, data analytics and data science – so I’ve always been working closely with data.
Why did you move to Singapore?
There’s too long a list of reasons why I moved to Singapore but the key ones are, food, food, food. 🙂 Apart from that, it’s nice to be closer to the rest of the world and Singapore serves as a great home base to explore other parts of Asia.
The main reason for my move was because Singapore is a hub for technological advancement in the region. The country has done amazing things around setting up infrastructure and an ecosystem that promotes innovation around tech. To put it simply, I wanted to be a part of that.
What is your role in Parcel Perform? Tell us about your daily routine.
My role here is a hybrid between a product manager and a data scientist. I build machine learning algorithms and the products which use these algorithms to improve the quality of the Parcel Perform product for both our customers and internal teams.
My day to day is very varied, which is a great way to make sure I’m constantly learning. Some days are spent entirely buried in Python Code doing data analysis, model building and evaluation. We’re lucky we have a strong data science team here at Parcel Perform who help with the technical side of machine learning too.
This means I get to spend more time thinking about how to present these models to our customers. It is very important with machine learning that the customer-facing products are easy to understand and use.
This makes sure customers can benefit from Parcel Perform’s vast amount of data and the complex models without having to dust off their statistics textbooks from back in University.
How is Parcel Perform different from your previous experiences?
Before Parcel Perform, the smallest company I worked for full-time had over 40,000 employees. Parcel Perform is a fair bit smaller in size from an employee perspective but it’s been really refreshing to see how much impact we can have at a global scale.
Rather than huge teams, we have lean teams where everyone’s skillset is so diverse that we can fill in each other’s gaps and build a very cool product.
What are some misconceptions of Machine Learning that you’ve encountered?
This is a tricky one, the list is quite long and growing because of the continued media hype, miscommunication and lack of understanding of machine learning. The fear around machine learning and machines replacing people’s jobs is also unfounded in my opinion.
I think machine learning and artificial intelligence will augment jobs, helping us spend more time focusing on the edge cases and improving overall results. Also, building, implementing and managing machine learning in production is a big task in itself, which will also create additional jobs.
I think the focus should be more on how we reskill people to transfer into the field, rather than worry about people being unemployed.
How does Machine Learning play a role in Parcel Perform’s operations?
Parcel Perform has troves of data from various carriers, customers and countries. This sets a very strong foundation for us to build on, creating machine learning tools and products which we can leverage to improve our internal processes and provide additional services to our customers.
If you could have a superpower, what would it be?
For me, I’d want the ability to teleport, so I could wake up on a beach in Australia and have a swim before coming to work in Singapore, have Turkish breakfast for lunch and go check out some new country after work.