Purva Malhotra
Deputy Manager @WNS
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WORK HISTORY
Deputy Manager @WNS
Supporting commercial and HEOR strategy by enabling faster, data-driven decision-making acrosstherapeutic areas-Developing Budget Impact Models (BIM) and Cost-Effectiveness Models (CEM) for multiple clientsacross therapeutic areas such as immunology, oncology, and rare diseases-Designing Markov and partitioned survival models to assess treatment pathways, calculate QALYs,ICERs, and incremental costs, and evaluate payer value propositions-Conducting systematic literature reviews (SLR) and targeted literature reviews (TLR) to identify modelinputs, clinical efficacy data, cost parameters, and health state utilities-Writing technical model documentation, validation reports, and methodological summaries in alignmentwith NICE, CADTH, and ICER guidelines-Working on creating an automated analytical tool to give a statistical summary using machine learning and LLM using Sparks via Databricks-Contributed to the development of an automated utility tool using PySpark to efficiently retrieve and process key performance metrics by NPI (National Provider Identifier), streamlining data access and reporting for healthcare analytics-Designed and developed end-to-end dashboards in Power BI, transforming complex datasets into interactive visual insights to support data-driven decision-making-Actively involved in pre-sales activities, including understanding client requirements, crafting tailored solutions, preparing proposals, and supporting product demonstrations to drive business growth.
EDUCATION
Institute of Actuaries of India
CT 3, Probability ad Statistics
Lancer’s Convent
Senior Secondary, Commerce
University of Kent
Masters, Statistics
St. Stephen's College, Delhi
One Year Certificate Course in German, Language German
Sri Venkateswara College, Delhi University
Bachelor's degree, B.Sc Mathematics (Hons)
ABOUT PURVA MALHOTRA
Statistician and Data Science professional with a strong foundation in real-world evidence (RWE), health economics and outcomes research (HEOR), and clinical trial analytics. I bring deep analytical rigor to solving healthcare challenges. I have hands-on experience working with large-scale real-world datasets (Optum, IQVIA) using R, PySpark, SQL, and SAS, delivering insights across therapeutic areas including immunology, cardiology, and rare diseases.My work spans causal inference modeling, market share analytics, clinical data transformation (EDC to SDTM/ADaM), and manuscript development for peer-reviewed publications. I’ve led and supported cross-functional teams on protocol development, SAPs, and regulatory documentation. I’m also passionate about capability building, having trained 200+ professionals in R, clinical programming, and statistical modeling.Driven by curiosity and precision, I aim to bridge data science with real-world healthcare impact.
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