Simran Yadav – Data Analyst at Centene Corporation

I didn’t have an extremely technical background, but I do have the capability of understanding and really digging deeper into the — Why’s of things

Simran Yadav is a Data Analyst with a focus on Predictive Analytics at Centene Corporation. Her inquisitiveness and interest in data made her pursue and complete a master’s in business data Analytics at the age of 22. Prior to that, she earned an undergraduate degree in Economics and Information Systems from Loyola University Chicago. She is a firm believer of the inclusion of women in tech and Science. She has been involved with various organizations focused on helping young women learn and get started with their STEM journey.

Outside her day job, Simran is also involved in forming the first university organization focused on Machine Learning at Loyola University Chicago. Along with that, she is also an Associate Editor for AI in Plain English — Medium which is a platform focused on publishing articles from around the globe about Artificial Intelligence (AI), Data Science and Machine Learning.

She believes that to “solve our current problems, we need to think differently than we have for ages and, to successfully do that, we need a diverse workforce”. 

In a Nutshell: Tell us a bit about your job and what role technology plays in it?

I am a Data Analyst with a focus on Predictive Analytics at Centene Corporation and will start working with their Provider Data Excellence team at the headquarters in St. Louis, Missouri. My key role in this team will be to support them in their move from descriptive analytics to predictive analytics. 

My core focus will be to identify how we can empower and deliver optimal Health plans and Insurance to our customers. Centene is a large Healthcare: Insurance and Managed Care Company, that provides services to government and private sponsored healthcare programs in the US and Globally. So, being the first candidate, they hired for their move towards automation, and Artificial Intelligence (AI) within the Analytics team is a great opportunity where I will be using my skills and education to creatively think of ways to provide the best service to our clients and drive business value leveraging data, analytics and AI. 

Where did your professional journey start and how did you get to where you are now?

I’d say about three years ago when I decided to study Information Systems while pursuing a Bachelor’s in Economics and International Relations. I was always more inclined towards humanities — social sciences but, I had to take an introductory class in business information systems which I genuinely enjoyed. Taking that class was a turning point. After that, I went on to further study Information Systems, get a Master’s in Data Analytics, do two internships while doing my Masters, and finally get a job as a Data Analyst. 

What is the greatest transformation in technology you have witnessed in your career?

The exponential growth in analytical technology. Collecting and analyzing data is seen as the main profit-driver in almost all organizations. Most multinational corporations like Google, Amazon, Microsoft rely on data and analytics for survival; they are currently storing and analyzing extensive amounts of data and varied types of it.

Another key transformation that is happening currently is the integration of AI and Machine Learning in analytics to achieve autonomous analytics. Businesses have really started to employ data-mining techniques and ML algorithms with descriptive, predictive, or, prescriptive analytics. Organizations are now moving towards predictive analytics by exploring “cognitive” technologies and automating the labor-intensive part and, having more humans involved in the decision-making and implementation process. And, as we move in the future, we will just see increased importance and use-cases of analytics. We can expect to see data-driven decisions being taken at all levels of business. Being involved in analytics myself, I am genuinely excited about how it’s uses and adoption change as we move more towards AI and automation. 

When you think about ‘women’ and ‘technology’ what comes to your mind first?

Looking on the brighter side, there is so much innovation and development in tech, and we experience that in our day-to-day lives. And yes, it’s exciting to see women in tech are coming into parity with men. 

More women involved in tech means more diversity, more innovation, increased creativity, increased financial returns, and low volatility.

But, is that it? Absolutely no, the numbers are not climbing rapidly enough! We still have a long way to go before we can reach gender equality. We require more women in technology to directly influence and achieve business goals efficiently. More women involved in tech means more diversity, more innovation, increased creativity, increased financial returns, and low volatility. I think, “women belong to literally every single place where decisions are being made.” 

We always hear there are not enough women working in Tech. What needs to happen to change that, which steps should be done to achieve gender equality in tech?

Since we have more male developers in IT, we are seeing increased biases in how AI and ML models are making decisions.

I think to have more female representation in tech we need a change on the very ground level. Foremost, we need to be more open as a society. To bridge that gender gap, we need to make efforts as early as — children’s elementary education. We need to be comfortable with the involvement of women in tech and sciences, in general. Furthermore, we need to focus on unconscious biases. Apparently, since we have more male developers in IT, we are seeing increased biases in how AI and ML models are making decisions. And, on a human level unknowingly, hiring managers and management can be involved in unfairness in the hiring process. These are really subtle things like the wording used in job postings or anything else that might come through as a gender-biased message. We also need more women included in the hiring process. And yes, there are roles that are exclusive for women, so I think workplaces should incorporate more flexible work-life strategies. For instance, the responsibility of child care mostly impacts women, so workplaces should be more pliable and provide some non-traditional work arrangements for women so that they are not eventually torn between their career and home.

Which was the best decision in your career?

Making the decision to start a career in Analytics and deciding to get a Master when I was just 21. My career path would have been radically different otherwise. I didn’t have an extremely technical background, but I do have the capability of understanding and really digging deeper into the — Why’s of things. Why are things, processes, businesses, the way they are? Through that, I am able to understand the ‘end value’ businesses are aiming to achieve and from there I work backward on how I can achieve those ‘end’ goals using technology. 

If you could go back in time, what advice would you give your 14-year-old self?

I think out of all things; I would follow my gut a bit more and be bold about seeking more opportunities. 

Just a suggestion to all young aspirants out there — Listen to what people have to say. But don’t feel the obligation to take everyone’s advice and act upon it. Get as much information as you can from whoever is kind enough to offer it to you, but know when to listen to yourself above all others – it’s your life, your career path and more often than not, you will know what YOU want to do, what YOU want to achieve.’

Simran Yadav is a Data Analyst with a focus on Predictive Analytics at Centene Corporation. Her inquisitiveness and interest in data made her pursue and complete a master’s in business data Analytics at the age of 22. Prior to that, she earned an undergraduate degree in Economics and Information Systems from Loyola University Chicago. She is a firm believer of the inclusion of women in tech and Science. She has been involved with various organizations focused on helping young women learn and get started with their STEM journey.

Outside her day job, Simran is also involved in forming the first university organization focused on Machine Learning at Loyola University Chicago. Along with that, she is also an Associate Editor for AI in Plain English — Medium which is a platform focused on publishing articles from around the globe about Artificial Intelligence (AI), Data Science and Machine Learning.

She believes that to “solve our current problems, we need to think differently than we have for ages and, to successfully do that, we need a diverse workforce”. 

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