The Story of Pramod Kumar Voola as Automation Engineer and Data Scientist

In this exclusive Q&A, Pramod shares his insights on leadership, innovation, and the future of healthcare technology.

In the ever-evolving fields of healthcare and technology, few professionals have reached the level of expertise and influence that Pramod Kumar Voola commands. With over seven years of experience, Pramod has been at the forefront of transforming clinical trials by improving efficacy and safety through cutting-edge technologies. As a resourcing manager with deep proficiency in data engineering and test automationhe has consistently driven teams to push the boundaries of innovation while maintaining strict compliance with life sciences standards—always with the ultimate focus on safeguarding human lives. In this exclusive Q&A, Pramod shares his insights on leadership, innovationand the future of healthcare technology.

Q1: You’re engaged in impactful work within the life sciences industry. How did you first become interested in this profession?

A: My interest in the life sciences industry began with the desire to be part of something larger than myself—something that has a direct, positive impact on people’s lives. It was during my work in clinical trialsparticularly focusing on patient safetythat I realized how technology could play a transformative role. The more I became exposed to automation and data engineeringthe more fascinated I became with the possibilities of data-driven healthcare.

Clinical trials are a critical component of medical research, but what truly intrigued me was the potential to enhance and improve these processes using advanced technologies. I found myself drawn to the challenge of making clinical trials more efficient, accurateand safe through the innovative use of automation and data systems. This passion for optimizing and advancing healthcare through technology is what ultimately led me into this profession

Q2: Can you share how you performed your leadership role in the course of working with the eCOA platforms?

A: Leading the development of eCOA (electronic Clinical Outcome Assessment) platforms was a pivotal moment in my career. These platforms are essential in collecting critical patient data from clinical trials, and my leadership role involved overseeing the management and validation of that dataensuring it adhered to the strict regulatory standards.

In this role, I was responsible for coordinating both engineering and testing teamswhich allowed me to bridge the gap between development and quality assurance within the same project. This holistic approach resulted in faster time-to-market for critical applications, significantly improving the delivery of clinical solutions while enhancing patient safety measures.

One of the most notable accomplishments was the development of compliance reporting tools that optimized the entire data processing pipeline. These reports provided us with real-time insights into the accuracy and reliability of the data, highlighting the importance of having the right information available at the right time for patient treatment. This leadership experience not only enhanced the efficiency of the platform but also reinforced the importance of data integrity and patient safety in clinical trials.

Q3: You’ve been a strong advocate for Artificial Intelligence in the healthcare space. What are some of the more prominent AI initiatives that you have undertaken?

A: For me, Artificial Intelligence is a transformative tool that has the potential to reshape patient care models and improve outcomes across the healthcare landscape. I’ve had the privilege of leading several AI-driven initiatives aimed at achieving these goals. One of the most exciting projects I managed was the development of GenAI-based chatbots for clinicians. These chatbots were designed to provide evidence-based care by delivering critical clinical information at the point of care and assisting both clinicians and patients in shared decision-making during crucial moments.

This initiative was part of a broader effort to integrate AI functionalities into healthcare delivery systems. The chatbots not only enhanced the decision-making process by making key medical insights readily available but also streamlined the interaction between patients and clinicians, helping improve overall clinical outcomes.

Q4: In the Role of Team Leader is a critical responsibility. What are the strategies that you employ as a leader and in creating a team?

A: For me, the true essence of leadership goes beyond simply achieving goals—it’s about becoming a source of motivation and energy for the team. From the outset, I see myself as both a mentor and a coachguiding my team members not only in terms of project success but also in the context of their career growth within the organization.

I prioritize creating a warm, inclusive, and collaborative atmosphere where each team member feels valued and appreciated. Fostering this kind of environment builds trust and openness, which are essential for effective teamwork. Naturally, in the course of projects, conflicts will arise. However, I believe in addressing conflicts through constructive engagement—this means actively listening to all perspectives, understanding the root of the issue, and working toward a solution that respects everyone’s interests.

Ultimately, teamwork is the foundation of any success, and the key to building a strong team lies in establishing trust, mutual respectand a shared vision. When every team member feels aligned with the common goal and knows their contribution is valued, that’s when the team truly excels.

Q5: Acquaint us with the technical difficulty you faced and how you managed it.

A: The task that was one of the most difficult, but turned out to be very gratifying too, is the creation of the data streaming pipelines in real time for a clinical trial project. At that point we were already using such tools as Snowflake and Apache Spark, Flink to process big amounts of data, and there were quite a few technical challenges that we needed to get through from data quality to compliance issues. I think the most difficult part was to get the tradeoff between the speed and accuracy because even the tiniest of errors in clinical data can lead to grave consequences. Fortunately, thanks to teamwork and a ceaseless demand for accuracy on a detailed level, we created a product that was capable of delivering business value without waiting for a proper characterization of the data.

Q6: What would you say is the most important thing you learned from your experience in testing and automation in Capital One Financial Services and how was that reflected in your subsequent positions?

A: My experiences at Capital one helped me in defining my automation and testing processes. I was at the forefront of strategies on developing and putting into action the use of automation testing for the Pega applications, which increased the coverage of tests as well as decreased the amount of manual work significantly. There, I also created portable and reusable automation interfaces, which then served as a springboard of my activities in the life science industry. When I stepped into the financial industry, I understood the level of attention to detail and discipline code is supposed to have. These are values that I carried over when I transitioned to working on healthcare applications. They are very similar in the regard that the processes and the stakes are high and there is need for automation to make sure the functioning of each and everything is up to routine safety and reliability.

Q7: Please let us know as to how you became interested in Data Science and its application in healthcare as you were already engaged in a Data Science certification at MIT at the time of interview.

A: I have always been dealing with data, be it while testing or in engineering, but I wished to take my skill set further to more advanced forms of data science. Working in healthcare, you realize that a lot of data is generated and the thrill of using that data to make better, quicker decisions was what intrigued me to pursue this certification. Through machine learning and predictive analytics, we can predict patient outcomes, optimize processes of clinical trials with substantial efficiency and realize the promise of personalized medicine. It’s all clear, and it’s obtrusive: healthcare is going to change due to data science. I am very keen to take part in that change, and work on solutions that will enhance the care provided to patients and the processes within clinics and hospitals.

Q8: Continuous improvement is subtle but very much present in the mentality of your teams while working on a product. How do you achieve that in a fast developing sector such as health technology?

A: It is one of the core values I have built within my teams. One cannot simply afford to remain idle in the booming healthcare and technology industries. We carry out a post mortem after every project in order to analyze and come up with the best tips that could make us better, be it in technical deliverables or communication. I am also happy to see people surrounding me being inquisitive and hence give them the reasons why it is important to always learn something. By embracing continuous improvement as a way of life, we not only improve upon the current work but also prepare the ground for the future by ensuring that we advance further with the changes within the industry.

Q9: What would you say is the most valuable lesson you’ve learned throughout your career?

A: Adaptability. The tech landscape is always changing and more so, more than any hard skill; this capacity is what one should value most in their professional selves. Personally, in my career, I have had to move with the changes in technologies, changes in industries, and changes in regulations. Maintaining a learning attitude, taking on new responsibilities, and changing the course of action have been the way forward for my evolution both as a leader and expert. I have made use of each of them to enhance the way I manage people in administration while inventing new technologies in dynamism.

Q10: The last question is about looking into the crystal ball, what are your future aspirations and how do you see yourself acting further?

A: In the future, I see myself deepening the convergence of AI, data science, and healthcare. It is necessary for me to continue working on solutions that deliver a real improvement in patient outcomes. Healthcare innovation is not only the creation of novel ideas or technologies, but rather, the implementation of these ideas and technologies in practice where they produce real impact. I also have a keen interest in training the future leaders in the fields of engineering and data science. I would like to encourage further innovation and the quest for knowledge, so that the innate potential in every individual can be helped to break through.

The way Pramod Kumar who started his career by doing automation testing of financial products has now diversified himself and is able to lead innovations in healthcare is an example of what a change in leadership and willingness to learn can accomplish. Patient experience and outcomes have been enhanced through his work in clinical trials, AI healthcare, and data engineering and have also elevated the pace of innovation within the industry. And as Pramod deepens his interest in the field of data science, it is clear to say that he will be part of the next evolution in technology within the sphere of health care.

First Published: 12 November 2022




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