Why We Need More Women Working in Data Science #DataTalk

We believe that big data is good. Good for our economy; good for consumers and good for society.

In a recent Experian #DataTalk, we had a chance to talk with Payal Jain about the importance of women and diversity in the data science industry.

Here is a full transcript of the interview:

Mike Delgado: Hello and welcome to Experian’s Weekly Data Talk, the show featuring some of the smartest people working in data science. Today we’re very excited to feature Payal Jain who is ranked last year as the number one big data influencer according to Data IQ Research. Payal has spent the last 15 years working in consumer lending industry in six different countries, and most recently serving as the managing director of strategic analytics at Barclaycard.

Aside from all of that work, she’s also a strong advocate for helping get more women involved in data science. Especially through her work with the Women in Data Science Conferences, which we’ll get to in just a bit. Today, we’re talking about that topic because there is a tremendous and disappointing gender gap in the data science industry.

Payal it’s a huge honor to have you as our guest today. Before we get started can you share your journey and what led you into working with data science.

Payal Jain: Thank you, Mike. It’s great to be with you today, and for everyone that’s listening. I started by doing a master degree all those years ago. Then I didn’t know what I wanted to do when I grew up.

So I craned the primary school teacher. I thought, I was passionate about math And I had a few bad math teachers along my way. I thought, well if I’m a teacher I can then rectify the whole education system.

I trained as a teacher and it wasn’t for me. I loved spending time with the children, but I’ve grown up in a very business orientated family. I started to look at what careers I could go into. Data science didn’t really exist. It was accounting, engineering, kind of some of this traditional thing.

It just didn’t sound like the job for me. A bit boring. I decided to have a gap year. My ambition was to start my gap year in September, work until Christmas, earn some money, then go traveling. Then go through the milk round after that. I started working for a gas company. I was there just to do some temping work. I was a PA, booking hotel rooms for some of the managers there. I thought, it will help me earn some money before I go traveling.

It was Monday morning, one of my weeks and I was looking a bit green in the face. One of the bosses walked past me and said, “You must have had a big weekend, what happened?” I said, “I graduated.” And then he said, “What did you graduate in?” I said, “Math.” He was like, “Where from?” I said, “Oxford.”

Then he said, “Why are you doing this job?” He literally picked me up and walked me around to their internal data science team, or the equivalent in those days. I spoke to the manager there and I thought, wow I never knew these types of jobs existed. It was around using your math skills in a business environment to solve the problem.

Mike Delgado: Yeah.

Payal Jain: It was fantastic. Within 20 minutes they offered me a job. I did it for a year and I loved it because it was bringing in that mathematical, logical way to solve problems, that are making a real impact on the business. It sparked my imagination. That’s kind of been my career since.

I went back to university for a year and did a masters in operational research, to kind of help bridge it. Then I joined Barclaycard on their graduate program and I haven’t looked back since.

Mike Delgado: That’s amazing. What an amazing journey, falling into data science with your background in math. Was there a specific area of data science that intrigued you?

Payal Jain: I love the analytics and the art around it. I truly believe there’s an art in the analysis. I’ve worked in multiple countries, as you mentioned earlier Mike. What’s great is that the methodologies and the way you work, can be the same. It doesn’t matter where you are, because the data structures are similar. But, for me, I love the analytical part. But, it’s around what are you going to do with that insightful data. That’s the bit that excites me the most. Until then, data is data. It’s there.

But until you’ve created the so what, you’re not using it for it to become insight. I think that my favorite part of the whole process Is what are you going to do with it? Whether it’s for the customer, for the company, making something better from a process perspective. Whatever it is. But it’s always the so what for me that I truly love because I think our viewpoint into that data is so privileged in an organization, that you have a different viewpoint that some of our peers around the table don’t have.

I think the privilege to have that, to then come up with new ideas of what to do with it.

Mike Delgado: I think you’re spot on. I didn’t know anything about data science at all, I was thinking, it’s just math, it’s just statistics, it’s someone sitting at a computer. But to your point, there’s so much art involved. The art in creating the right question, because if you don’t have the right question, you don’t even know what kind of data to be looking for.

Payal Jain: That’s right. Totally agree.

Mike Delgado: I want to talk a little bit about the gender gap, that you observed. I was looking at some research and seeing that 40% of graduates are women. Statistics is a very important skill set, for a data scientist, as you know. But we’re not seeing a lot of these graduates move into data science. I think there’s a variety of reasons, but I’m curious. What’s been your perspective, having been working in data science for 15 years and working in six different countries?

Payal Jain: To start with, it’s important to me that it’s not just about getting and promoting women into data sciences roles. I think what’s important is diversity and recognizing diversity.

Diversity comes in a few different forms. Gender is one, which is the simplest in that you can see it when you walk into a room. But introverts and extroverts are another element of diversity. You’ve got all sorts of styles of how people operate that represents diversity.

What I’m passionate about, Mike, is having teams with diversity because that diversity reflects on who your customers are, who your internal stakeholders are. Because we’re talking to populations that have equal diversity across them. If we recruit for people like ourselves, we then become a little bit too similar in our thinking. And we don’t manage, and respect, and think about our true stakeholders. I think that’s a really important part of it.

But your observation is right in that there are less women in data science verses some of the other functions in an organization. Surprisingly, we’re even behind the curved versus technology. In some sectors in the UK, for sure, I think that’s a bit where you think we must solve it. Because that’s not right.

I think that’s important to recognize.  The difference between gender is generalizing, but I’ve seen it quite a lot when I’ve been building themes and interacting with different organizations of people, that men tend to get promoted for potential. They will sell themselves into a job.

Women tend to get promoted for past accomplishments. I see it all the time, where I’ve got people that work for me and my teams or other people I’m mentoring. Where some of my female mentees will say, “But I’m not ready for that, Payal.” I think, well why not? Let me challenge you against it.

When they’re in an interview, they’re trying to say, this is why I’m not right. Whereas some of their male counterparts may say, “This is why I fit into it.”

As an interviewer, you’re listening to that and you think, who do I take? The person that’s confident, or the ones that’s telling me they’re not quite ready yet. That’s the bit that we need to understand and have awareness of to make sure that we recognize that in organizations. Then, it’s not about changing our attitudes, but it’s being aware of it. And making sure we get our questioning right, to encourage people. The people that we’re interviewing and talking to, and mentoring in our teams, to encourage them to actually take it to the next level.

Mike Delgado: I love hearing your perspective as a leader and as you’ve conducted so many different interviews.  That perception of how men versus women are being interviewed for positions, you’re looking for somebody who is going to be confident, who is going to be creative, who is going to fit well with the team.

At the same time, to your point, you also want diversity. You want to make sure that you have a diverse staff because you have different stakeholders. You want diversity in, not only gender, ethnicity, but also in the skill sets. Physics, statistics, having those different types of skills sets can all add tremendous value because everyone that has different perspectives will a different opinion on how to solve a business problem.

Payal Jain: That’s right.

Mike Delgado: As you have been an advocate in, obviously, speaking at the Women in Data Conference. Have you received any criticism personally about the work that you’re doing?

Payal Jain: It’s been fascinating. The Women in Data Conferences, we’re coming up to our third conference this autumn. In year one, we were feeling a little bit nervous in terms of going into that. Thinking about, what will people think? We decided to just invite women only, and we thought will women want to come to such an event? What will some of the male counterparts say?

We were really interested to see what will happen, but we did think there was a need to have it. To have that forum where people can be open and talk about some of the challenges. We’ve been astounded by some of the reactions.

You know, for all the people that have attended or heard about it, through other colleagues, when they’ve gone back and spoken about it they think, wow. I wish I could have come, or it was great to hear other women’s stories and things. If they can do it, I can do it.

When they talk about some of their experiences and how their challenge and certain situations, environments, they think I’ve had exactly that. How did you get through it? They want to hear the stories. It’s fantastic to see there’s such a need for it, for that population. But, the ambition for women in data is around changing the trends and getting more women into some of the senior roles, and changing the trend in organizations

We’re not there. The trend hasn’t changed. We’re still kind of working towards that, but we’ve had a couple of reactions as we’ve been talking to some of our senior counterparts and organizations. Where some have said, “I don’t just want to go out and recruit women. It’s the wrong thing.” They’re always surprised when I say, “I agree with you. You should always recruit the person that is most qualified for the role.” I stick to that today, it’s really important. You take the best candidate for the role.

Even if your team is low in terms of men or women, you should always say, “Who is the best person for it?” But acknowledging diversity is really important. We should recruit our own kind of makeup.

What’s important is awareness. That is the bit that people don’t quite understand what women in data are trying to say is, when we’re trying to encourage some of our female counterparts to be confident. But secondly, we’re saying to other leaders, you’ve got to be aware of some of the things that these people are going through. That you need to, as a leader, watch out for.

I’ve also had the opposite, where I was talking to an organization and they said, “Actually, yeah. You’re right. All my team are men. We’re just going to create a female campaign.” I said, “That’s good, but you need the diversity. We need the mixture around the table. Just having one type of person around the table is ineffective for any team.”

What’s fantastic with women in data is we’ve seen the size of it double every single year. We have 450 females coming to our conference this autumn. This year, for the first time, we’re going to get a couple of male speakers coming in to hear their perspective of the value that they’ve seen when they’ve built teams with diversity.

Mike Delgado: That’s awesome. I love your perspective about hiring the right person. That’s ultimately the job of the leader. With your point, the whole point of the conference is to drive that awareness that leaders need to be more aware of the diversity within their teams.

Payal Jain: Yeah.

Mike Delgado: I was reading this study from the Peterson Institute for International Economics, it was a partnership with EY. They did a study of 21,000 globally public companies, and 91 different countries. So, it was a very diverse study.

What they found was that companies with more women in the C-suite, tend to be more profitable than those companies with fewer women. So, it was very concurring research showing the value of women in the C-suite. From your perspective, what sort of leadership roles would you like to see women have in data science?

Payal Jain:  To start with, it’s great to see that stat being proven through research, because it’s something I truly believe. And are 100% passionate about. If I think about some of the leadership teams I’ve been part of, it’s great to have that diversity around the table because people think about things in different ways.

Coming back to your question around what types of roles should women be aspired to be and in data science, I think it’s all of them. It’s not one particular type, or one particular field. Truly, the field as a whole in data science, would benefit from having women at all levels wanting to get there.

Now, it’s really important to say not all women want to go and be the C-suite person, for personal reasons. Maybe they’ve got other priorities, or they just want that balance in their life. They don’t want the stress of being a leader in a company. That’s why I say it should be at all levels.

But, what I don’t want to see are people being held back, or thinking I can’t get there because of these limitations. That’s the piece that we want to kind of stop and encourage that trend to change. At the same time, again, it’s that awareness. I know I’ve said it a few times, off the board, a leadership team to say, “Actually, having some of that diversity within the team, and having a potentially female chief data officer, may bring this dimension in that we haven’t thought about.”

Again, it’s making sure that we’ve got women in all levels. But, what I don’t want to see going forward, is someone saying, I just don’t think I can get there. Because I think anything’s a possibility. It’s our role to try and encourage that individual, but also the organizations to think more broadly about it.

Mike Delgado: Payal, I don’t know if you’ve been watching what’s happening here in the states, especially in the tech area, there was a Google memo that went around that was very disturbing about the perspective and biases against women. And things that are happening at other companies.

Obviously, if this is happening at some of the biggest companies in the world, where there’s these perceptions, how do women begin to enter these male dominated data tech teams? What would be some advice you’d give these women?

Payal Jain: I think the biggest thing is about confidence. It’s being confident, or pretending to be confident. That’s necessary in order to reach for opportunities. I use “pretending” to be confident, because sometimes inside we may feel nervous, or think, I can’t do it. But you have to portray that you can.

There’s this great book that I’m sure most of you have heard of by Sheryl Sandberg saying, lean in, fit around the table, and be part of it. The book is great, but you just need to look at the title and it tells you what the book is about. It’s around confidence in being part of it because, again, when you’re talking to someone that is trying to hire people, and they’ve got someone that isn’t confident, they’re going to think, “I just need someone that’s going to walk in and start the role. Contribute. And do the job that we’re looking for them to do.”

I just think that’s so important. But, there are points where we all have that piece where we’re not as confident. I’ll give you a story. When I was working for a private equity company, and they flew me to New York. And we were in this amazing board room, I’ve never seen a board room so big. It was 50 seats wide, and beautiful oak table, overlooking central park. It was amazing.

They flew me over for 20 hours, I left the UK, arrived at night. We had a meeting, slept for a couple of hours and we were in the office. I thought, for me, I’ve not worked in this environment of investment banking. There’s a different between UK culture and an American culture. I’ve lived and worked in other countries, so, I’ve been exposed to it. But, it’s different.

Then the meeting started and I walked into the meeting room. Saw this huge table, and I started to feel a bit nervous. Then they said to me Payal, you’re sitting here. It was right in the middle of the table. It was a key point where, I was opposite the key guy that was making the decisions.

Then, as people started to walk in, I looked around and out of 50 people, there were 49 men and myself.

Mike Delgado: Wow.

Payal Jain: My heart fluttered. I just thought, this is a different environment. It’s an environment where, again, I’m used to working in a male dominated environment. I’m a confident person. But I had that moment of, wow. Take a breath.

Again, it’s around being confident. I know my expertise, I knew my material. It’s taking that breath, recognizing yourself, but just saying I can do it. I think that’s hugely important.

But, I do say it’s around being confident, but pretending to be confident. Because even if you’re having that fluttering inside, it’s to say, I can do it. And I will, and I did.

Mike Delgado: Payal, I love that. Pretending to be confident. That’s a big part of it because people go into interviews and to your point earlier, confidence is a huge factor. Is this person going to be able to accomplish the task I’m going to give them?

If they are appearing confident, look like they’re going to be a strong worker, this is somebody who is going to probably stand apart from the others. Confidence is a huge thing. I love how you’re saying, if you don’t have that confidence, at least pretend to have that confidence. Just take it on because if you have the skill set, you can do it. You just have to portray it.

Payal Jain: Exactly that. We have to be confident in order to reach for opportunities. It’s very seldom things just come to you. Sometimes you must fight for it and grab it. Coming back to where we started of talking about how women kind of trying to tell you why they’re not ready for a role. Whereas guys will come in and tell you why they are ready.

It’s the same thing. It’s just really important that we’re aware of that. You can train around it, you can do whatever you need to do before you walk into a meeting like that. But you’ve got to go in and say, “I can do it.”

Mike Delgado: Payal, I don’t know if you saw, but in Harvard Business Review, I think a couple years ago, it said that data scientist is the sexiest new job. I was looking at some data from a job search engine, Indeed.com, showing the trend line for the amount of data science positions that are being offered. It’s like a hockey stick. Data science roles are all over the place as more companies are bringing on AI and other emerging technologies and bots, etc.

I’m curious for the women that are listening in, that are thinking about, I like what Payal is saying, I would like to get involved in data science. What would you say would be some steps they can take to begin down that path? To begin learning. What advice would you give them?

Payal Jain: The most important thing about wanting to do something is passion. If you’ve got the passion to want to do it, you’re half way there. Every company, even those that you wouldn’t naturally think about, they’re talking about data. Now talking about data is just everywhere.

I think it’s such a fantastic field to go in. When I graduated, we’d never heard of it. Now, there’s so much opportunity. It’s about getting involved. You can take courses at home, go and join a class somewhere. I know in the UK there are a lot of meet ups where people meet in the evening and they’ll share and talk about things.

Just get involved. Start to meet other people that are doing something similar, get on with some training so you’ve got the technical skills to start coding in whichever language you want. But the piece I would encourage is always to think about the, “so what.”

How is this data going to help me do something better? That’s when you move from being a programmer, to a true data scientist. Where you’re making an impact on the business or whatever the challenge is you’re trying to solve.

Mike Delgado: Getting to the so what, why does this matter? That’s ultimately what’s going to help the business, it’s going to help the business, it’s going to help you in that role. It goes back to what you said in the very beginning about the art. The art of data science is having those questions, being curious. If you’re curious by nature, data science might be for you.

Payal Jain: Exactly. You know, what’s great is you can be as creative as you like. One of the things I loved in some of my early roles, and even today, is the idea you come with today, you can test it tomorrow. And you see the results so quickly.

It’s the speed as well, in terms of which you get feedback and you start seeing the data. It’s truly exciting and exceptional.

Mike Delgado: Awesome. Before we go I know you’ve been heavily involved in the Women in Data Conference there in the UK. Can you share with everyone a little bit more about it? How they can get involved?

Payal Jain: The conference is happening in November. Like I said, we’ve got 450 females that are attending this year. For those people in the UK, I can send you a link, Mike. They can log on and register that they’d like to be an attendee. So, they’ve still got the option to register. I’ll do that just to follow up.

For those that aren’t in the UK, we are videoing a lot of the talks on that day. So, again, you’re welcome to go and have a look at the talks from last year, as well as the year before. They’re all available on the websites. Then, you can link in to November, when the new links will be available.

But the most important thing, it’s around starting to talk about this. And encouraging the people that we sit next to, by having the dialogue of some of the challenges, some of the things of how we overcome things as well is really important to talk about. So, I think the conference is one piece, but hopefully it becomes a norm in us talking about it.

It’s amongst our female colleagues, as well as our male colleagues. I just had a great conversation with a colleague now as I was preparing to come here, and he was saying, “What are you doing?” Then he told me a story about him interviewing a couple of people, and what happened. He said, “I’m so much more aware of this.”

I think that’s the important part. We shouldn’t just be talking about this toward females, but actually it’s a whole colleague sets. And to some of our customers that we should be talking to this about.

Like I said, we’ll forward you the link, Mike. It’ll be great if you can share it to a lot of the listeners.

Mike Delgado: Yes. In fact, what I’m going to do here, is I’m going to put it here on our screen. It’s WomenInData.co.uk, I’ll also put the link in our comments on Facebook. As well as when we upload this to YouTube, I’ll have it in the about section, so it’s very easy for people to click on over to learn more about the conference.

Definitely check it out there. Amazing speakers at that conference, lots of good stuff going on. I would love at some point if maybe the conference could come to the states. I think it would do very well over here.

Payal Jain: Yep. Fantastic. We may just do that.

Mike Delgado: Payal, it’s been an honor talking with you. Thank you so much for all of your work in data science, especially for being the advocate for diversity in the data science fields. Thank you so much for sharing your insights with us.

I want to thank all the viewers here for all of your likes, your comments, your shares. As you know, we do this data talk every single week. And I learn a ton from our guests. So, Payal, thank you so much for being our guest today.

I want to remind you, if you want to learn more about the work that Payal is doing, you can go to the Experian Data Talk website. The URL is just Experian.com/datatalk.

You can get information all about Payal, how you can connect with her on Twitter, as well as on LinkedIn. Of course, you can always go to WomenInData.co.uk to learn more about her work and connect with her there.

Payal, thank you so much for being our guest. For everyone else, we will see you all next week. Take care.

Payal Jain: Thanks.

Mike Delgado: Bye, Payal. Thank you.

About Payal Jain

Payal is this year’s number 1 in the DataIQ Big 100.

Payal has recently moved on from her successful role as Managing Director, Strategic Analytics at Barclaycard, part of a varied career having spent the last 15 years in the consumer lending industry where data is at the heart of the business. She has worked in six different countries, where she learned the similarities and differences in consumer behaviour..

Payal started life as a SAS analyst, assessing the effectiveness of marketing initiatives. She quickly learned that spending time understanding the data in combination with appreciating the marketing and business context enabled her to talk to stakeholders on the true insight of the data and, through using this insight, to them solve their business problems. Payal recognises this helped accelerate her career.

Her successful roles have been a triangle between analytical, commercial and credit risk skills where her knowledge and understanding of data has truly helped her succeed.

Make sure to follow Payal on Twitter, LinkedIn, and her work with WomenInData.co.uk.

Check out our upcoming live video big data discussions.