Data Science - AI ML

WNS, part of Capgemini, is an Agentic AI-powered leader in intelligent operations and transformation, serving more than 700 clients across 10 industries, including Banking and Financial Services, Healthcare, Insurance, Shipping and Logistics, and Travel and Hospitality. We bring together deep domain excellence - WNS’ core differentiator - with AI-powered platforms and analytics to help businesses innovate, scale, adapt and build resilience in a world defined by disruption.Our purpose is clear: to enable lasting business value by designing intelligent, human-led solutions that deliver sustainable outcomes and a differentiated impact. With three global headquarters across four continents, operations in 13 countries, 65 delivery centers and more than 66,000 employees, WNS combines scale, expertise and execution to create meaningful, measurable impact. Overview We are looking for a seasoned in Advanced Analytics for the Lifesciences/Pharma domain. The person will lead a dynamic team focused on delivering AI-driven analytics solutions across Marketing, Sales, Medical and Commercial Operations. Proficiency in Machine Learning, Deep Learning, NLP, Generative AI, Large Language Models (LLMs), Commercial and Omnichannel Analytics and Python/PySpark is essential. Roles and Responsibilities Partner with client Advanced Analytics teams to identify, scope and deliver analytics and AI solutions that solve business problems and generate measurable business value. Deliver projects across marketing mix modelling, promotion effectiveness, ROI analysis, portfolio analytics, segmentation & targeting, omnichannel analytics, Next Best Action (NBA), forecasting, resource optimization and other commercial analytics engagements. Develop analytical and AI solutions supporting pharmaceutical sales, marketing and commercial operations. Stay current with statistical, machine learning, deep learning and Generative AI methodologies to recommend the most appropriate analytical approaches. Develop AI/GenAI Proof of Concepts (POCs), reusable accelerators and standardized analytics frameworks. Lead multiple projects independently while managing small teams of Analysts/Senior Analysts to deliver high-quality solutions. Ensure timely delivery with strong focus on quality, client satisfaction and agreed SLAs. Drive structured project execution through effective planning, documentation and stakeholder communication. Explore emerging AI, GenAI and advanced analytics techniques to enhance business decision-making. Drive automation using reusable code, AI-assisted workflows and scalable analytics solutions. Maintain knowledge repositories, reusable assets, SOPs and quality frameworks to improve delivery efficiency. Build new analytical capabilities, identify business opportunities and support organizational growth. Contribute to whitepapers, capability building, internal assets and thought leadership initiatives. Develop and deliver presentations and recommendations to senior client stakeholders during delivery and business development. Support recruitment, onboarding, mentoring and knowledge-sharing initiatives across the team. Ensure compliance with organizational processes, governance and quality standards. Additional Information Strong interpersonal and client communication skills. Excellent leadership, collaboration and stakeholder management abilities. Strong analytical thinking and problem-solving mindset. Storyboarding and storytelling skills to translate analytics into business insights. Ability to manage multiple priorities in a matrix organization. Passion for continuous learning, innovation and adoption of emerging AI technologies. Strong commitment to quality, ownership and customer success. Eligibility Criteria Required Experience 4–10 years of experience in Advanced Analytics, Data Science or AI. 2–4 years of experience in Healthcare, Lifesciences or Pharmaceutical Analytics is preferred. Strong quantitative, analytical and problem-solving skills. Ability to quickly understand new datasets and translate them into business insights. Experience working with global teams and cross-functional stakeholders is desirable. Proven ability to deliver measurable business impact through analytics and AI. Technical Skills Proficient in Python, PySpark or R for machine learning and statistical modeling with exposure to SQL; SAS or Alteryx is an added advantage. Expertise in Regression, Classification, Clustering, Bayesian Models, Time Series, NLP, Feature Engineering, Recommendation Systems and Generative AI techniques. Experience building and deploying Deep Learning models including CNN, RNN, LSTM and Transformer architectures. Experience in Omnichannel Analytics including Marketing Mix Modelling, Next Best Action, customer segmentation, campaign optimization and Pharma CRM analytics. Hands-on experience with NLP, semantic search, chatbots, document summarization, question answering and information extraction. Proficient in GPT, Claude, Gemini, Llama, LangChain, LlamaIndex, Prompt Engineering and Retrieval-Augmented Generation (RAG). Hands-on experience with Azure, AWS or GCP along with Python, Docker, Git and deployment of scalable AI applications. Experience with visualization tools such as Tableau, Power BI or Qlik. Strong project management, documentation and presentation skills. Pharmaceutical commercial analytics knowledge is highly desirable. Good to Have Skills Exposure to Databricks, Spark, Hadoop, Hive, Feature Stores, Vector Databases, MLOps/LLMOps and Responsible AI practices. Knowledge of optimization techniques, stochastic models, Markov Chains and Multi-Touch Attribution. Basic Qualifications B.Tech/Masters (or equivalent) in Computer Science, Statistics, Applied Mathematics, Data Science, Bioinformatics, Operations Research, Econometrics, Economics or related quantitative discipline. Excellent written and verbal communication skills in English. Graduate