Women in Tech: “Curiosity and support are essential for STEM careers”
Women are underrepresented in the tech sector —myth or reality? Three years ago, we launched a diversity series aimed at bringing the most inspirational and powerful women in the tech scene to your attention. Today, we’d like you to meet Dr. Xuxu Wang, Chief Data Officer at PredictHQ.
A research study by The National Center for Women & Information Technology showed that “gender diversity has specific benefits in technology settings,” which could explain why tech companies have started to invest in initiatives that aim to boost the number of female applicants, recruit them in a more effective way, retain them for longer, and give them the opportunity to advance. But is it enough?
Three years ago, we launched a diversity series aimed at bringing the most inspirational and powerful women in the tech scene to your attention. Today, we’d like you to meet Dr. Xuxu Wang, Chief Data Officer at PredictHQ.
Today’s Woman in Tech: Dr. Xuxu Wang, Chief Data Officer at PredictHQ
Dr. Xuxu Wang is the Chief Data Officer at PredictHQ. She brings comprehensive data science and advanced machine learning expertise, as well as industry-leading intelligence product R&D insights after more than a decade of experience of leading R&D teams at Baidu in Beijing and Workday in California. Within her role with PredictHQ, she is responsible for data intelligence R&D, machine learning features, and product R&D and intelligence product development. She both grows and leads a team of data scientists, engineers, and analysts that work on complex challenges such as event impact prediction models to make sense of millions of events worldwide. Dr. Wang is passionate about using data, algorithms, and building intelligence to make an influence on the world. Outside of work, she is an avid lover of hiking, history, and food.
When did you become interested in technology?
As a little girl I wanted to be an astronaut. I always loved science and used to lie down in the backyard of my grandma’s place and look up at the night sky, wanting to be up there exploring. So as soon as I could apply to university, I enrolled in a top science university in China to study rocket science.
I hold a Bachelor and Master’s in Aeronautics and Astronautics, and a Ph.D. in Machine Learning. If I followed the same path as most of my courses’ alumni career paths, I would be working as a rocket scientist for China’s National Space Agency. But I was lucky enough to get to work on a very interesting project for my master’s degree where I learned that my real love was data science.
The project was developing the machine learning models to power the first multi-channel polygraph detector. It was a unique and pioneering project developing time series models and machine learning models to understand and compare inputs from multiple physical sources. It enabled us to identify anomalies in a person’s physical responses when lying. It was a very interesting project because it used complex technology and critical thinking, as well as unique field trips such as going into prisons to interview prisoners to collect data to train our model. We successfully created the multichannel polygraph detector that is still in use today.
More importantly for me, though, was to discover I was more intrigued and excited by data science than rocket science. My first data science role was at Baidu where I got to work with trillions of data points every day. I went on to become the technical product manager for Baidu Adwords, which was an incredible opportunity to learn about data science at scale, as well as leading teams and innovating.
Did you receive support from your family and friends?
My family has always been very supportive and both my father and my grandfather were engineers and my great-grandfather went to France in the 1920s to pursue his Ph.D. in physics. I believe it is really important that girls get support from family members when they find themselves fascinated and excited about technology and science.
I still remember when I built my first toy boat as a six-year-old. I used steam technology to power my toy boat by having a glass bottle of water with a candle under it which I learned from the story my grandma told me about how James Watt invented the steam engine. It wasn’t a successful roadshow of my first toy boat — unfortunately, it exploded after seconds in the pool. I was scared, but not stopped by the accident. I succeeded with my second steam toy boat with help from my dad and my grandma, before going on to build my first electric toy boat together with my grandma where I used electric machinery from one of our mini-electric fans.
As I discovered at an early age, curiosity and support are essential for STEM careers. The rise of learn-to-code programs has made it seem much more normal for girls to explore these careers and to have peers who are exploring and enjoying the same topics.
Did someone ever try to stop you from learning and advancing in your professional life?
Unfortunately, every woman in tech is going to encounter people on their journey who they will need to overcome or avoid. For me, it is more interesting to look at the patterns that hold women back from technical roles rather than the handful of difficult individuals that I have had to face as I learned and grew into my professional life.
The best thing we can do is keep believing in ourselves, to take pride in our work, and to support other women around us.
I’m all too familiar with the gender gap in technical fields. I was one of 10 women among 400 students during my first year in the college engineering program. I remember my childhood teachers encouraging the boys toward math and science and the girls toward arts and social studies. While in primary school, I was the only female participant in the National Math Olympics.
I still remember when I built my first toy boat as a six-year-old. I used steam technology to power my toy boat by having a glass bottle of water with a candle under it which I learned from the story my grandma told me about how James Watt invented the steam engine.
A day in Xuxu’s life
As PredictHQ’s chief data officer, I work with my team of 20 data scientists and analysts to build out models that fuel our knowledge graph. My team has built more than 1,000 machine learning models to aggregate and verify millions of events, which our customers use to inform their demand forecasting. Even though COVID-19 has caused a brief pause in concerts, sports, and similar events, there are still thousands of impactful events every week such as school holidays, observances, severe weather, and natural disasters. To find, verify, and then rank these by predicted impact, my team has to be very creative and focused.
My typical workday starts long before I get into the office. I spend my mornings and evenings reading up on the latest data science trends and technologies so PredictHQ is always right at the forefront of our thinking and approach. Data science is evolving so quickly and there are so many brilliant researchers publishing their work as open source. You need to be knowledgeable about these techniques and thinking so you can make use of all the latest research for the benefit of the business.
Once I get to work, we start with a daily stand-up for both our data intelligence and data assurance teams. I know a lot of data scientists prefer deep work on their own- and I love that too. But your dream as CDO is to build world-class products using the best and latest technologies – but you can’t do that alone. So you need to build a world-class team and keep imagining and encouraging every team member to think bigger and work well together.
From there, I spend my day problem solving the individuals and teams that need it, or working with the wider company to ensure we can deliver the data science teams work effectively and efficiently. Being a CDO requires me to work closely with developers, product teams as well as broader business-focused executives.
In the afternoons and into the evenings, I will often work directly on new models or data science frameworks for our intelligence product. It is important to keep in touch with your craft, and this enables me to take some of the cutting edge processes I’ve learned about and bring them to life for PredictHQ. Data science is still a reasonably new field and doing pioneering work in any field is daunting, so as a data leader, it is my job to lead the way with new technology. For example, we completely rebuilt our machine learning deduping model on entirely new technology recently; deciding to do that as a team was challenging. There was no evidence that our proposed innovative route would work – we just knew that every existing model we could find didn’t deliver the elite results we wanted for PredictHQ.
What are you most proud of in your career?
I have two elements of my career of which I am very proud. The first is the world-class and world-first demand intelligence products and features I’ve built together with my world-class data science team at PredictHQ. From Aviation Rank, our unique Machine Learning dedupler, to Beam, towards the world-first live-TV predicted Viewership, we are building those world-first demand intelligence features and products. I am proud of seeing how our work has been adopted by some of the world’s largest companies, and added a lot of value to their operations.
Why aren’t there more women in tech? Could you name a few challenges (or obstacles) women in tech face?
Lots of women study data science and data analysis – we need to do a much better job at supporting them in their careers. This includes better recruiting, better training opportunities, more consideration for promotions, and recognizing that women face additional challenges in the tech industry in general.
Because technology has been a very male-dominated space, we need to work hard to create an inclusive culture for women from their pre-career in university all the way up to leadership roles. Data leaders and tech leaders need to work closely with people and culture teams and the wider executive team to ensure their company is a supportive culture for everyone.
Would our world be different if more women worked in STEM?
One of the things many people underestimate about data science is how creative you need to be successful. The greater diversity we have in STEM, the more creative the industry can be. Whether it’s an individual person joining a team with a fresh perspective on the world because of their life journey, or a team that can benefit from a wide range of interests, the idea that STEM and especially data science should be dominated by men with doctorate degrees is an attitude that needs to evolve.
The more women we have in STEM, the wider diversity of thought we have to create more ambitious technology to build and solve the problems we seek to solve. Data science is really only just getting started, and the opportunities ahead of us for machine learning are breath-taking. We are going to need as many types of people as we can get!
Within our own teams, we can get more women into data scientist roles if we remove boundaries that men don’t face and recognize not every data scientist has to come from academic backgrounds, which can also be male-dominated. If you are committed, many excellent data scientists who are women can emerge from senior data analyst roles if you invest time and training into them.
We know that women have to feel 100% confident they can do a job before volunteering or applying, whereas men are happy to give it a try at 60% confident – good leadership mentoring can help mitigate this.
Data science is really only just getting started, and the opportunities ahead of us for machine learning are breath-taking. We are going to need as many types of people as we can get!
The discussion about diversity is gaining momentum. How long will it take to see results from the current debate?
We are already seeing results but we are still a long way from parity. It shouldn’t be unusual or noteworthy for women to work and lead in STEM.
Until a woman can head data or development teams and companies with no one finding that remarkable, we are not there.
What advice (and tips) would you give to women who want a tech career?
Never stop believing in yourself and never stop learning. Data science is a new field and it will look radically different every few years.
My hope is that not only will we be achieving unbelievable results in a few years, but also that the industry will be a far more diverse one than it is now. To get there, we are going to need everyone who wants to be part of it to find their place, and to encourage their peers to keep learning, growing, and achieving great innovations.
More Women in Tech:
- Women in Tech: “Celebrate your wins, big and little”
- Women in Tech: “Experiment, deliver, retrospect, and keep learning!”
- Women in Tech: “You are the best author of your own career path”
- Women in Tech: “Dare to do what you are interested in!”
- Women in Tech: “Join meetups and other women tech groups”