Lead Data Scientist

We are hiring a Lead Data Scientist - Pharma Analytics to lead client-facing analytics engagements and deliver advanced AI/ML solutions for global pharmaceutical organisations. The ideal candidate will possess deep expertise in Pharma Commercial Analytics, Marketing Analytics, Machine Learning, Advanced Analytics, and Data Science delivery, with strong hands-on experience in Python, SQL, Cloud technologies, and pharma datasets. The role requires balancing technical excellence, stakeholder management, and team leadership while translating complex business problems into scalable analytics solutions.

The candidate will have responsibilities across the following functions

Analytics and Solution Delivery:

• Partner with business stakeholders and clients to understand business challenges and translate them into analytical solutions.
• Design and deliver scalable data science and advanced analytics solutions.
• Lead end-to-end analytics projects from problem definition through deployment and impact measurement.
• Develop predictive models, forecasting solutions, machine learning algorithms, and optimisation frameworks.
• Drive insights generation through statistical modelling, machine learning, segmentation, forecasting, and performance analytics.
• Present actionable recommendations and storytelling-driven insights to senior client stakeholders.
• Team Leadership Internal Use Only Lead, mentor, and develop a team of Data Scientists and Analysts.
• Conduct technical solution reviews, code reviews, and mentoring sessions.
• Drive adoption of best practices across Data Science, AI/ML, Cloud, GenAI, and Analytics delivery.
• Ensure high-quality and timely project execution.

Client Engagement:

• Collaborate closely with Pharma Commercial, Marketing, Brand, Sales, Market Access, and Strategy teams.
• Participate in solution design, capability building, proposal development, and client presentations.
• Build strong relationships with senior stakeholders and act as a trusted analytics advisor.

Requirements:

• Advanced proficiency in Python.
• Advanced proficiency in SQL.
• Strong expertise in: Machine Learning, Predictive Modelling, Statistics, Hypothesis Testing, Feature Engineering, Model Validation, Forecasting, Data Visualisation: Power BI (Preferred), Tableau (Alternative).
• Cloud exposure in at least one of: AWS Internal Use Only, Azure, GCP.
• Skill Mix 1: Commercial Pharma Analytics.
• Mandatory Pharma Analytics Experience: Hands-on experience in one or more of: Commercial Analytics, Sales Analytics, Market Analytics, Brand Analytics, Performance Analytics, Forecasting Analytics, Pharma Data Sources.
• Strong working knowledge of at least some of the following: IQVIA Symphony Health, MMIT Truven Health, Jump Prescription Data, Claims Data, Patient-Level Commercial Data.
• Preferred Use Cases: Sales Force Effectiveness, Territory Alignment, Targeting and Segmentation, Commercial Performance Measurement, Incentive Compensation Analytics, Launch Analytics.