#DigitalEmpowersUs Interview Series: Women in Tech with Bayer's Nalini Polavarapu

Nalini Polavarapu has always been interested in taking an interdisciplinary approach to solving challenges on a global scale. She currently works as the Head of Data Sciences – Customer Centricity at Bayer. With a strong foundational background in STEM coursework, she developed a lifelong passion for AI and agriculture which she has been able to combine when she began her work as Bayer’s first data scientist over 10 years ago. Since then, the team has vastly expanded and the overall data science community within Bayer Crop Science alone employs 700 + people. I sat down with her learn more about her experience as a woman in the tech industry and advice she would give to women looking to follow a similar path. 

— Alexa Miller, Director, Digital Empowers National Campaign

Who is your wonder woman?

My wonder woman is Melinda Gates for her noble commitment to improving the lives of many underprivileged people across the world and how she is generously using her time, resources and influence to achieve the same. I admire and adore her.

Describe your current work in tech and the impact it has made on the community and/or consumers.

What drove me to this opportunity was the unique chance to innovate, develop a team, and to further the digital transformation of Bayer. While we faced challenges bringing AI inventions into a field that had yet to engage with it, we were able to make impactful progress. The inventions sparked by my team, including predictive modelling for better seed outcomes, will foster food security for 9 billion people by 2050. Today, my team’s work is a major component of Bayer’s innovation toolbox, improving both our products and the customer experience.

Talk to us in more detail about some of the other women’s and/or social impact projects you’ve worked on in your career.

In my career I have had the opportunity to both further projects for society, and develop internally a culture inclusive of women. With my work, we are able to use AI algorithms and predictive modelling to forecast seed performance before they are planted. This has allowed us to test 5 times more corn varieties in the research pipeline, improve sustainability, and enhance farmers’ lives. Using these techniques, we are enabling the farmers of tomorrow to feed a growing global population, without using more water, energy or land. 

Internally, I lead Bayer’s Women in Data Science Group. In this role, I engage with women in the field of data science at Bayer, and women in other city chapters. In March for instance, I will be in Chicago speaking on a panel at a Women in Data Science event focusing on how to increase women in technology. I’m also involved with the CIO, CDO and CAO forums and venture groups, to help executives and entrepreneurs understand AI and machine learning, and how they can leverage these technologies to digitally transform businesses and to solve major societal issues.

Changing the focus of this question slightly, instead of the biggest hurdle you faced as a womAn in tech—how did you think about the opportunity that you had as not just first data scientist at Bayer, but how under your leadership you could affect the recruitment, retention and promotion of women in data science roles?

As with other STEM fields, there are very few women in data science. Generally speaking there are only around 10-15% women in data science. Bayer is no different from this trend and for many years there was only a small representation of women. Bayer as a company has recognized this and is dedicating time on diversity and inclusion and bringing more diverse groups into different technology fields, including data science. The company also has put a focus on elevating more women to leadership levels. So as a company it is doing quite a bit of work to address the hurdles for women in tech. 

As a leading voice at Bayer, I have worked to demonstrate the need for female voices in leadership, and gained senior leaders’ buy-in for making those changes. When we started hiring more women in data science, we started it primarily in the crop science division. Bayer however is a multi-divisional company, we have crop science, pharmaceuticals and consumer health focus areas. I was able to achieve buy-in of the senior leaders from other divisions, as well as their support and influence. Stemming from this, recently we had a global launch of Women in Data Science, which is across all divisions and geographies. The response was phenomenal for the group, from senior leadership all the way to the people working on the ground.

Speaking holistically, what are the biggest hurdles for women in tech?

Speaking broadly, the experiences, expectations, or challenges that women have may not be the same as others, so it’s important to pay attention to those. I’ll give you some examples, and these don’t just apply to women, it applies to everyone as well. 

One example is work calls, sometimes we may have to take early morning meetings and if you have young kids at home it may not be the same. Paying attention to those small things when there are others involved and providing flexibility is important. One item that hiring managers often say is that they want to hire more diverse candidates, but that they don’t see the talent or they don’t have anyone to hire, then the question is did you look hard enough?

What advice would you give to women trying to break into engineering and technology fields?

Know what you’re passionate about and don't hold yourself back! If you are able to do this and find your champions, the doors will open.  Something that I should have done in my early career is speaking up for my needs that may be different from my male colleagues or that I just generally needed assistance with. I was a little uncomfortable because most of the time the people or teams that I reported to were almost 90% men. That describes the environment I was in for most of my career. So I tried to adapt myself to how the culture was, rather than asking for help. I didn't feel comfortable with asking and I felt like I was often stretching to meet the norms. Also, people will be open to making accommodations if you ask, it is more achieving that comfort to ask for help. 

Today, people are paying a lot more attention to inclusion. So now, an employee does not have to accept certain things just as the norm. Once someone voices their need, people will be open to accomodating. 

Any closing sentiments?

I will leave you with this: Find your ‘champions’ and don’t ever hold back just because you are a woman. If you are passionate about your work, you will excel and bring significant value to the field.