Employer description & source details
Data Science and Analytics Solution Delivery Partner with clients and business stakeholders to understand business challenges, define analytical problems, and develop appropriate data science solutions. Lead end-to-end analytics engagements, from problem definition and data exploration to model development, deployment, and impact measurement. Design and implement scalable advanced analytics, machine learning, and AI solutions for pharmaceutical business requirements. Develop predictive models, forecasting solutions, optimisation frameworks, and analytical algorithms to support commercial and marketing decision-making. Apply statistical modelling, hypothesis testing, feature engineering, segmentation, and model validation techniques to generate meaningful insights. Translate analytical findings into actionable recommendations through clear, data-driven storytelling and presentations. Deliver analytics solutions across pharmaceutical sales, commercial performance, brand performance, market intelligence, and forecasting. Analyse prescription, claims, patient-level commercial, and other relevant pharmaceutical datasets to identify trends and business opportunities. Develop solutions for sales force effectiveness, territory alignment, customer targeting, and segmentation. Support commercial performance measurement, incentive compensation analytics, product launch analytics, and market share analysis. Use pharmaceutical data sources such as IQVIA, Symphony Health, MMIT, Truven, and HealthJump, where relevant. Collaborate with commercial, sales, market access, brand, and strategy teams to address business priorities through analytics. Design and deliver pharmaceutical marketing analytics solutions to measure campaign effectiveness and optimise marketing investments. Develop an
Extracted skills: python, sql, aws, azure, gcp, machine learning, data analysis, power bi, tableau, sales