NAVYA SOMESH

• Lead the design and implementation of Next Best Action (NBA) recommendation engines to enable precision HCP targeting and personalized engagement strategies
• Guide teams on RPC (Remote Personalization Channels) and SLS (Sales & Launch Systems) to ensure seamless omnichannel execution during product launches
• Built Agentic AI solutions to automate extraction and structuring of feature definitions from complex pharma datasets including FLR, PMPX, and Kedrion data frameworks
• Developed intelligent pipelines to transform unstructured medical and commercial data into structured, actionable insights , accelerating decision-making and reducing manual dependency
• Act as a technical bridge between business, data science, and engineering teams , ensuring scalable and production-ready AI systems

•Managed recommendation engines for two major drugs (BKY and TRO) for Gilead, generating $500M revenue for BKY within 6 months.
• Built the TRO recommendation engine from scratch, achieving minimal errors at the first go-live.
• Cross-trained employees to enhance team agility and optimize performance.
• Streamlined budgets, ensuring optimal resource allocation and business growth investments.
• Mentored junior staff, fostering career development and leadership potential.
Reduced operational costs through comprehensive process improvements and resource management initiatives.
•Led a team of data scientists in developing and implementing complex predictive models to drive strategic business decisions.
• Outlined and implemented plans to meet operational targets.
•Built agentic AI agents to manage dynamic medical Q&A workflows, enabling autonomous follow-ups, contextual understanding, personalized response delivery, and escalation to providers, improving patient support and care coordination.

•Developed multimodal Agentic AI agents for healthcare Q&A, capable of interpreting clinical text and medical images (e.g., X-rays, pathology scans) to deliver accurate, personalized answers and escalate findings to care teams when necessary.

• Spearheaded the development of the Incremental Customer Lifetime Value (ICLV) recommendation engine, enhancing customer value through targeted recommendations.
• Engineered a comprehensive ML Modeling interface, enabling autonomous data analysis and decision-making in adherence to Ethical AI principles, incorporating conversational interfaces like ChatGPT, and achieving an 80% client acceptance rate through effective visualizations.
• Launched the Genesis project to pinpoint high internet penetration areas, assisting clients in establishing internet services and gaining a competitive advantage over existing providers.
• Utilized Binary Classification Models to pinpoint and mitigate customer churn influenced by service changes, pricing, competition, and non-payment, resulting in a 30% reduction in churn rates Improved service, billing, and retention outreach by solving a meticulous classification problem to prioritize call queues, enhancing payment compliance and boosting retention by 25%.
• Implemented predictive analysis and clustering techniques to identify customers likely to adopt new services, optimizing cross-sell opportunities.
• Conducted fan segmentation using machine learning techniques such as K-means, CHART, and RFM models to tailor engagement strategies to diverse customer behaviors.
• Developed image captioning solutions for digital content shared with customers, employing state-of-the-art models like InceptionV3, LSTM, visual attention, and Word2Vec.
• Initiated a proof of concept for a language translator capable of converting video audio content into the user's preferred language, utilizing cutting-edge models like RAG.
• Facilitated the deployment of large language models, leveraging magnetic and Fast Chat technologies for enhanced performance and user experience.

• Led a team of 9 in pioneering the Data Bias Mitigation project to detect and neutralize data biases, enhancing ethical AI practices.
• Spearheaded the Green AI initiative, significantly reducing the environmental impact of AI by optimizing neural networks for lower energy consumption.
• Engineered innovative algorithms to assess and minimize carbon emissions from machine learning models, promoting sustainable AI development.
• Utilized Transfer Learning techniques to analyze and predict customer behaviors during natural disasters across Australia, improving crisis response strategies.
• Created Cheddar CBA, a highly successful social media-based deal aggregator that personalized offers and generated $650M in revenue.
• Developed and maintained the Regional Movers Index dashboard for the Australian government, providing crucial insights on demographic shifts and predictive modelling.