Senior Manager – Data Science(Job No 676)

• Work closely with clients to comprehend their requirements and varied objectives including (but not limited to) implementation of Omnichannel strategy
• Lead the assessment of existing ecosystems across key pillars, including client portfolio plans & objectives, technical architecture, data models etc
• Collaborate with cross-functional teams to design and implement the optimal solution, ensuring seamless integration with existing processes
• Leverage pharma industry exposure to provide strategic insights and recommendations for stated client objectives
• Demonstrate proficiency in understanding and working with diverse pharma datasets, and assess their suitability for integration into the proposed solution
• Apply data science skills, with expertise in MLOps being a significant plus, to ensure robust and scalable model deployment
• Foster strong client relationships, serving as a trusted advisor and ensuring client satisfaction throughout the implementation process
• Provide training and support to internal teams to ensure smooth and continued success on project implementations
• Handle multiple projects at any point in time, ensuring that progress is made across all the projects, with appropriate prioritization and workload distribution within the team
• Develop and disseminate innovative analytical techniques, processes and tools, that can be leveraged across projects / engagements
• Support business development activities by building new capabilities and participating in client meetings as a subject matter expert
• Provide thought leadership by contributing to whitepapers and articles at the BU and organization level

Qualifications:
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• Bachelor's or Master’s degree in Computer Science, Data Science, Pharmaceutical Sciences
• 9+ overall years of experience in leading analytical projects in pharma domain
• 7+ years of experience advanced analytics including AI, machine learning, predictive modelling, advanced analytics and statistics modelling
• Experience in pharma commercial analytics is a plus
• Proven track record of successfully implementing omnichannel strategy or similar technologies in the pharmaceutical or related industry
• Strong understanding of the pharma ecosystem and familiarity with key data sources (Digital, sales, CRM, APLD), industry trends, and compliance requirements
• Excellent understanding of machine learning techniques and algorithms, such as XGBoost, Random Forest, Linear, Logistic Regression, k-NN, Naive Bayes, SVM, Decision Trees, Neural Nets, Transfer Learning, NLP etc
• Experience in areas of risk-score modelling, customer segmentation, impact assessment, attribution analytics, collaborative filtering, marketing mix modelling, recommendation engines and natural language processing is highly preferred