Jegatheeswari Perumalsamy

16 October 2024

Jegatheeswari Perumalsamy, a Senior Lead Data Analyst, has been driving innovation in data architecture for over 17 years, with extensive experience in insurance and banking. Her roles at organizations like Athene, Tata Consultancy Services (TCS), Cognizant Technology Solutions (CTS) and IBM have cemented her expertise in data analysis, data modelling, and cloud-native technologies.

Throughout her career, Jegatheeswari has led the design and implementation of complex data architectures, focusing on creating scalable solutions tailored to the unique needs of industries like annuity and life insurance. Her experience in data modelling has enabled organizations to transition from traditional data systems to more agile, cloud-integrated frameworks, significantly improving accuracy of the data, operational efficiency and data quality.

Jegatheeswari leverages her analytical skills to dissect complex datasets, uncovering patterns, trends, and correlations. Her insights provide a clear picture of the company’s performance, market position, and operational efficiency.

Her work ensures that the company’s data infrastructure can handle increasing data volumes without compromising efficiency. By staying updated with new modelling techniques and technologies, Jegatheeswari drives innovation in data structuring.

How has your research on AI and Machine Learning influenced your work in data architecture? Can you share some specific projects where these technologies made a significant impact?

Jegatheeswari’s research on Artificial Intelligence (AI) and Machine Learning (ML) applications has been transformative in the field of data architecture. Through her scholarly work, she has explored how AI/ML can enhance the accuracy and efficiency of data systems. “AI/ML allows us to automate processes that were once manual and time-consuming, such as data profiling, anomaly detection, and data governance,” she explains.

In one of her notable research projects, Jegatheeswari used AI models to identify patterns in investment data. We applied AI to streamline data management processes, particularly in identifying critical data elements (CDEs) vital for business decisions. This has improved both the accuracy of data and the proactive nature of data quality assurance.”

Her research on data quality has also delved into optimizing data warehousing through machine learning algorithms in ETL (Extract, Transform, Load) processes. This continuous monitoring of data quality ensures actionable and reliable insights for decision-making.

What do you see as the future of AI and ML in data architecture? How will these technologies shape the industry in the coming years?

Jegatheeswari envisions a future where AI/ML will lead to self-governing data ecosystems. “We’re moving towards systems where AI will play a larger role in predictive analytics and risk management,” she predicts. For industries like insurance, AI can dynamically assess risk profiles, enabling more personalized underwriting and policy offerings.

She also highlights the importance of data governance in this AI-driven future. “AI systems will soon manage data integrity in real-time, ensuring compliance with regulatory requirements while improving the efficiency of data management processes,” Jegatheeswari notes.

When it comes to challenges, data security remains a primary concern. “Ensuring that AI-driven systems adhere to security standards while protecting sensitive data is crucial,” she emphasizes.

You have contributed to numerous scholarly papers on AI/ML. Can you share insights into some of your most impactful research and its application in real-world scenarios?

In addition to her professional achievements, Jegatheeswari is an active contributor to the academic and technical community. She has authored and co-authored numerous papers on topics such as AI-driven data governance, real-time fraud detection, and cloud computing.

Her notable work, “AI-Driven Solutions for Data Quality in Financial Services”, examines how machine learning algorithms can maintain the integrity of financial data in real-time. “The goal of this research was to address the pressing issue of data accuracy and timeliness in financial services,” she explains. By applying AI to data governance, Jegatheeswari’s research shows how data inconsistencies can be identified and addressed proactively.

She has also explored predictive analytics in insurance, researching how AI can predict policyholder behavior and improve customer retention. “Predictive analytics allows for more informed decision-making in underwriting and claims management,” she adds.

You’ve received prestigious awards like the Titan Awards. What do these recognitions mean to you, and how have they influenced your professional journey?

Jegatheeswari’s work in data architecture and AI has earned her multiple awards, including the prestigious Titan Awards and the Indian Achiever Forum’s International Achievers Award. These accolades recognize her leadership in data innovation and her contributions to automating processes within the insurance and financial sectors.

Winning the Titan Award highlighted her team’s efforts in creating cutting-edge solutions to real-world challenges in data management. She has also been recognized by the Indian Achiever Forum for automating data workflows at organizations like Bank of America and Citi.

How has being an IEEE Senior Member benefited your career? In what ways has it helped you grow and expand your network?

Another significant milestone in Jegatheeswari’s career has been her elevation to IEEE Senior Member status. “IEEE has expanded my professional network and created opportunities for collaborative research,” she notes. Through IEEE, she stays updated on the latest trends in data architecture and machine learning.

Jegatheeswari also values the mentorship opportunities offered by IEEE. “Mentoring younger professionals is one of the most rewarding aspects of my career,” she says. By guiding the next generation of data architects, she ensures that they are well-prepared for the evolving challenges of the industry.

Where do you see the intersection of cloud computing, AI, and automation taking data architecture in the future?

Jegatheeswari is optimistic about the role of AI and cloud computing in shaping the future of data architecture. She envisions a world where AI-driven automation will enhance data quality and enable companies to be more agile in responding to market changes.

“Cloud-native architectures powered by AI and machine learning will lead the way,” she asserts. These self-governing systems will enable industries like insurance to scale data systems while maintaining integrity and accuracy.

Data security remains a top priority as AI-based solutions gain momentum. Jegatheeswari is already exploring ways to integrate AI with security protocols to mitigate these risks.

You’ve been active in mentoring young professionals. How do you approach mentorship, and what advice do you give to those entering the field of data architecture?

Mentorship plays a central role in Jegatheeswari’s career. She actively mentors young professionals, guiding them through the complexities of data architecture and cloud computing. “Mentorship is something I value deeply,” she shares, noting that it’s her way of giving back to the community.

Jegatheeswari also participates in industry conferences and workshops, where she shares her expertise on data architecture, AI, and cloud technologies. Her goal is to foster a culture of collaboration and continuous learning in the industry.

Jegatheeswari’s research papers continue to influence the field. Her work on “AI-Driven Data Governance in the Insurance Sector” examines how AI can automate compliance processes while improving data quality. In another key paper, “Real-Time Data Integration for Predictive Analytics in Financial Services,” she explores how AI enables real-time decision-making for financial institutions.

You emphasize the importance of balancing innovation with practicality. How do you ensure that AI solutions are both innovative and aligned with business needs?

While Jegatheeswari advocates for AI-driven innovation, she also emphasizes practicality. “For AI to be effective, it must complement existing systems rather than disrupt them,” she advises. Her pragmatic approach ensures that AI solutions provide immediate value while aligning with business objectives.

As a female leader in the tech industry, Jegatheeswari is passionate about promoting diversity and inclusion. She actively participates in initiatives aimed at increasing the representation of women in STEM and mentors young women entering the field.

Jegatheeswari’s work continues to earn her recognition. In addition to the Titan Awards and the Indian Achiever Forum accolades, she has received internal awards for her leadership in data architecture projects. These recognitions reflect her commitment to staying at the forefront of data architecture and AI innovation.

Through her research, leadership, and commitment to mentorship, Jegatheeswari Perumalsamy has established herself as a visionary leader in data architecture, AI, and cloud computing. As she continues to explore new frontiers in AI-driven data innovation, her work will undoubtedly shape the future of technology in the insurance and financial services sectors. Her dedication to advancing the industry through scholarly contributions and fostering the next generation of professionals ensures that her impact will be felt for years to come.