Aruna Pattam is a seasoned AI leader with over 22 years of experience. She is currently the head of AI and data science at HCL Technologies for Asia Pacific, Middle East and Japan.

Aruna has completed her master’s in data science and has extensive experience in delivering solutions using data analytics, artificial intelligence, and machine learning. Earlier, she has held many technical and executive leadership roles in Commonwealth Bank of Australia, Westpac, AMP financial services, and SAS Australia. In an interaction with Analytics India Magazine, she discussed her journey in analytics and AI.

AIM: What made you pursue a STEM career?

Aruna Pattam: Just like many girls, after finishing high school, I took the non-technical stream and pursued business administration and then went on to do an MBA. I had an interest in computers, but I was afraid it was too complex, so I stayed away. When I migrated to Australia and got an opportunity to study, my interest in computers sparked again. I entered a postgraduate computer and information science program. I was so inexperienced that I didn’t know how to insert a floppy disk into the computer. 

Initially, it was a little hard coming from a non-technical stream but my sheer interest and passion in the subject kept me going, and that helped me to complete my postgraduation.

AIM: How did you get into AI and analytics?

Aruna Pattam: When I was doing my last year of postgraduation, my university organised the campus interview, and I was fortunate enough to be offered a role – one was in networks, and the other one was with SAS, a global analytics company. Without much idea about analytics, but impressed by the flexibility and how supportive they were during the interview process, I took up the role in SAS. And, as they say, the rest is history!

Maybe I was destined to be in analytics, because once I started working with data, I just loved it. The more I worked with data, the more passionate I became about discovering insights from data and helping organisations make better decisions.

AIM: What are the major challenges you have faced in your career? How did you overcome them?

Aruna Pattam: As a woman in the STEM business, I’ve undoubtedly encountered my fair share of problems over the years, particularly during my early years.

• Imposter syndrome

Despite the fact that I had a technical background, when I began my STEM career, I still felt like an impostor and didn’t feel comfortable enough. The thought that I didn’t know enough and that I am probably lucky to get the job, stopped me from putting my hand up and taking on new challenges. It took me a long time to accept and believe that it is acceptable to not know everything and asking for assistance is absolutely fine. As a result, I began seeing it as an opportunity to learn new things and it developed my confidence. Once I started thinking that way, my self-esteem shot up, and I started accepting new challenges.

• Dealing with the ‘bro culture’

There have been times when I was the only woman in a meeting or on a project team. And I’ve been in situations where I’ve felt that my ideas haven’t been taken seriously or that they believe I’m not capable of it. It can be frustrating, but instead of feeling defeated, I took it as a challenge. I started speaking up more. I also made it a point to build relationships with the key decision makers in the company. By doing that, I was able to gain their trust and respect, and my ideas were finally being heard.

• Work-life balance

STEM careers are demanding, and it can be difficult to find a balance between work and life. I’ve often found myself working long hours and weekends, and it’s taken a toll on my personal life. It’s been a challenge to find that balance.  However, over the years I have learnt the art of time management and how to better manage my workload by learning to delegate and ask for help when needed. I’m also trying to make more time for activities that I enjoy outside of work. I’m now able to find a healthy balance between work and life, and I’m passionate about helping others to do the same.

One important factor that helped me overcome these challenges was my mentors and role models, both inside and outside of work. I was very fortunate to have found women I could look up to and who gave me the advice and support that I needed to succeed. Despite all these challenges, I’ve loved every minute of my STEM journey. It’s been an amazing ride, and I’m excited to see what the future holds.

AIM: What’s your biggest professional achievement?

Aruna Pattam: Over the years, I have delivered many greenfield projects as well as set up teams from the ground. But if I had to pick one, then it would be my current role as head of AI and Data Science managing Asia Pacific, Japan and Middle East region for a Global Technology organisation that has presence in across 52 countries. Aside from my role, what excites me currently is being able to lead as a women’s advocate in these regions. I am also very excited to be part of Microsoft’s diversity and inclusion initiative, Code without Barriers, for which HCL is a proud partner. It gives me great pleasure to be able to mentor women as part of this programme. Being able to help other women grow in their STEM careers is extremely fulfilling, and I feel very lucky to be able to do what I love every day.

AIM: What are the traits you look for when hiring a data scientist?

Aruna Pattam: There are many traits that make a good data scientist or AI professional, but the most important ones I look for are:

• Curiosity: A successful data scientist or AI professional is always curious and wants to learn more. They are constantly asking questions and looking for new ways to solve problems.

• Creativity: A good data scientist or AI expert will have a creative side and is willing to think outside the box. They’re able to see things in new ways and come up with innovative solutions.

• Passion: Someone who is passionate about their work and loves what they do. They are always excited to learn new things and take on new challenges.

• Technical: Having good technical skills is very crucial. They should be able to code, have experience with various data analysis techniques, and understand machine learning algorithms. 

•  Communication: Another important trait is being able to communicate effectively. A good data scientist should be able to explain their findings to non-technical people in a clear and concise way.

AIM: Why do you think data science and AI continue to be a male-dominated space?

Aruna Pattam: There are a number of reasons behind this, but I think the biggest one is that women have been traditionally underrepresented in STEM fields. There is an assumption that women can’t do maths or science. This makes it hard in getting girls interested in STEM subjects due to their negative experiences and lack of encouragement.

• Bias against mothers taking time off work for family caregiving duties. There is a myth that mothers who take time off work to care for their children are less committed to the workforce and ultimately, not as valuable as men.

• Women often lack confidence and feel like they don’t have the skillset to work in a field such as AI.

• Lack of female role models: There are few female mentors within the industry and a lack of mentorship programs for females at all levels within companies.

• Lack of visibility: Many of the job opportunities just aren’t as visible or well-advertised where they’re needed most – making it difficult for women to reach them.

This is changing, but it’s still an issue. I believe that if we can get more women interested in STEM fields, the data science and AI field will have much more gender balance.

AIM: How do you encourage women to take up STEM roles?

Aruna Pattam: 

• Encourage girls to take STEM classes and get involved in STEM activities from a young age.

• Provide mentorship and support to women who are already working in STEM fields.

• Make sure that women have access to the same opportunities and resources as men.

• Encourage women to have confidence in their abilities and pursue STEM careers.

• Increase visibility of women in STEM fields through media representation and positive role models.

• Implement policies that help to close the gender gap in STEM fields.

• Provide training and resources that help to eliminate bias against women in STEM fields.

• Encourage companies to invest in initiatives that support women in STEM.

AIM: How do you see the AI and analytics space evolving?

Aruna Pattam: There is no doubt that AI and analytics will continue to grow in popularity in the near future. With the advancements in technology, more and more businesses are beginning to realise the potential of these fields. I believe that we will see a lot of innovation in the way that data is collected and analysed, and this will lead to better decision making and improved outcomes for businesses. 

We will see a continued innovation in AI tools and technologies and an increase in these AI tools for tasks such as predictive maintenance, fraud detection, prediction of diseases, personalised products and services etc. We will also see more emphasis on Responsible AI, as businesses become more aware of the potential ethical implications of AI. Overall, I believe that the future of AI and analytics is very exciting, and they will become more mainstream and integrated into everyday life.