The Drum's 'Unsung Heroes' series is a celebration of the people in the industry who slog hard behind the limelight for their companies, brands, and clients. As they are seldom in the spotlight for their contribution to the success of campaigns, this is their time to shine.
Dr. Ian Anderson, the head of data science at InMobi, says he focuses on a lot of the great work happening via other groups/teams in his industry and seek to emulate their best practices and insights. That is why he tends to focus on learning from other data science teams as opposed to individuals.
Why is your job important?
I am somewhat lucky in that in 2012 the Harvard Business Review called out the role of the data scientist as “the sexiest job of the 21st Century.”
Since then, machine learning (ML) and artificial intelligence (AI) continue to grab the headlines due to the positive impact they have on business efficiency and the opportunities they create.
For a business to succeed in this day and age, it cannot ignore this and I’d suggest instead it must adopt an AI-first attitude.
What is the most difficult and stressful part of your job?
One of the most difficult parts is getting others outside of the group I work in to understand how time-consuming solving a particular problem is.
Some tasks that we work on are actually very simple from a data science perspective and can be completed in a relatively short amount of time, whereas others may appear similar to someone on the outside but can, in fact, be many times more complex and require significantly more work.
Communicating this and educating others can be tough at times as often the person with the ask is under pressure to deliver to the customer quickly.
What is the most rewarding part of your job?
I’m lucky in that there are many parts of my job that I enjoy and find rewarding for different reasons. If I list a few, they would include:
Working with sales teams on technical data-focused tasks that they don’t think are possible, as delivering this work provides immense satisfaction, knowing that I have helped.
Giving people back time by helping them automate a task that has previously taken them a number of hours to complete on a regular basis is a great feeling, as I know I am making that person more productive by giving them the most important commodity of all.
I enjoy the requirement to continually learn new skills and improve, alongside evolutions in the state-of-the-art in my field. On the one hand, it’s somewhat depressing to know that the best practices in data science, ML and AI will have been superseded by new approaches in the next 18-24 months as it requires quite a time commitment to keep up.
But the continued learning is exciting and the changes in our field are profound and generally focus on improving efficiency (giving back time), alongside some radical new developments such as deep learning techniques focused on image recognition.
First thing that comes to people’s minds when you tell them your job?
*Laughs* Well, I normally just say ‘I’m a data nerd’ and then see how interested they are in hearing more before I go into the real details of what my job involves.
I find a lot of people on first hearing this imagine a white lab coat, perhaps a stereotypically poor set of communication skills with an overly complex and theoretical manner of describing my work.
How would you correct/explain to them what you do then?
I normally start by getting a sense of their own role and technical expertise and then tailor the description of my role with that in mind.
For example, if I am speaking to a fellow Data Scientist, I might explain what I am working on in the context of machine learning and our approach to model tuning.
However, if I am speaking to someone in a more non-technical role I might focus more on the output of our work and what kickstarted its development.
Is there anything you want to change in your job?
I’d love the opportunity to remove all of those last-minute asks that are critical but need to be delivered tomorrow :-)
Which campaign, that you worked on, are you most proud of?
The campaigns I have enjoyed working on the most are those that involve custom requirements from the advertiser and require a deeper working relationship perhaps with my counterparts on the advertiser side (data scientists).
Joining advertiser data with our own datasets often allows for some fascinating insights to be derived and completely new approaches to targeting users.
I find I learn a great deal of domain-specific knowledge and get to think more deeply about the problems due to the need to answer questions that I had perhaps not considered before. This mutual exchange of ideas and approach to work is always very rewarding.
Who is someone you want to emulate in your industry?
I focus on a lot of the great work happening via other groups/teams in our industry and seek to emulate their best practices and insights.
There are many people involved in making a data scientist successful, and this includes everyone from engineering providing the infrastructure so we can do our work, to creative and sales teams that set interesting and new problems via customer needs, to the product development teams with forthcoming requirements.
Given this, I tend to focus on learning from other data science teams as opposed to individuals.
If you weren’t a data scientist, what would you be?
I’m not really sure I can answer that. I love my job and the area I work in, but if I didn’t I would like to think I’d have done something about it to fulfill that aspiration.
Perhaps a role in the video game industry, but I’m not sure if enjoying playing video games would translate to being good at creating them!
We have closed submissions for Unsung Heroes as the series has ended. You can read the previous feature on the multimedia developer, here.