Jul 2020 – Feb 2023 · 2 yrs 7 mos · Hyderabad · Hybrid

• At Novartis, I led the convergence of data engineering, real-world evidence, and advanced analytics to support drug development, clinical trials, and commercial strategy. Managing hybrid global teams across engineering and analytics, I built a culture of collaboration, precision, and delivery velocity, enabling insights that advanced both scientific decision-making and business growth.
• I championed cloud-native data platform modernization, designing scalable ETL/ELT pipelines and automated workflows in Databricks and Snowflake to accelerate data readiness for clinical and commercial use cases. I implemented data governance and quality frameworks including standardized business definitions, metadata and lineage tracking, and reproducibility controls to ensure trust, consistency, and regulatory compliance across research and commercial analytics workflows.
• On the analytics side, I led the design of marketing mix and attribution models, as well as patient adherence and segmentation models, guiding omnichannel engagement strategy through experiment-driven insights and real-time feedback loops. These initiatives improved targeting precision, optimized spend allocation, and supported trial and therapy progression outcomes.
• This role strengthened my capabilities in LLMs, Generative AI, predictive modeling, and RWE analytics, while deepening my ability to lead cross-functional, science-aligned, and commercially actionable data product development.

Sep 2018 – Jul 2020 · 1 yr 10 mos · On-site

• At Franklin Templeton, my work centered on bringing advanced data science into sales strategy and decision-making. I designed and deployed recommendation models that reshaped how financial advisors were targeted, making sales outreach sharper and more efficient.
• To ensure long-term adoption, I introduced KPI frameworks, scorecards, and performance metrics that turned analytics into actionable growth strategies across multiple regions. I also built analytics capability within the organization, launching intensive training programs that upskilled 40+ professionals and embedded a culture of evidence-based decision-making.

Feb 2017 – Aug 2018 · 1 yr 6 mos · United States · On-site

• At Evalueserve, I focused on elevating customer experiences through data-driven insights. By applying AI-powered real-time engagement strategies, I improved customer journeys and strengthened retention.
• I also developed predictive segmentation models that combined machine learning with behavioral analytics, enabling sharper campaign personalization and higher conversion impact across multiple markets.

Oct 2013 – Dec 2015 · 2 yrs 2 mos · On-site

• Worked on advanced analytics initiatives to strengthen data management and customer insights. Designed and implemented a data archiving solution that optimized storage efficiency, reduced operational overhead, and created new revenue opportunities through better data utilization.
• Applied machine learning techniques, including KNN clustering, to analyze loyalty card and behavioral data, uncovering patterns that enabled targeted offers, refined segmentation, and improved cross-selling performance.

Sep 2010 – Sep 2013 · 3 yrs · On-site

• At Wipro, I worked at the intersection of data quality, reporting, and process analytics, supporting enterprise clients in the Energy & Utilities domain. I developed real-time dashboards to monitor IDOCs, EDI, and batch data transfers, enabling early issue identification and smoother business operations.
• I also designed and automated daily data quality reports, ensuring accuracy across large customer databases and accelerating the resolution of discrepancies. These projects laid the foundation for my expertise in data visualization, data management, and process optimization that I built on in subsequent data science role