QUALIFICATION REQUIRED :

A master's or doctoral degree in a relevant field such as applied statistics and mathematics, data science, computer science, operations research or a related discipline.

EXPERIENCE REQUIRED :

- 8-12 years of experience in commercial analytics/decision sciences, in the pharmaceutical industry.

- Proven experience in managing and delivering complex projects within the pharma analytics domain.

- Strong expertise in commercial analytics like Multichannel Marketing Mix Measurement & Investment Optimization, Campaign Analytics , HCP/Account Segmentation and Performance Analytics etc.

- Preferred experience in Patient / Market Access / Sales Analytics.

- Experience leading and mentoring teams on complex analytical projects.

Technical Skills :

- Advanced knowledge of statistical analysis tools and programming languages such as Python, R, SAS, SQL, etc.

- Strong understanding of AI/ML techniques and their applications in decision sciences.

RESPONSIBILITIES :

Project Planning and Delivery (Operations) :

- Lead the strategic planning and execution of projects within the Decision Sciences vertical.

- Collaborate with cross-functional teams to define project objectives, deliverables, timelines, and resource requirements.

- Ensure effective project management, including scope management, risk assessment, and mitigation strategies.

- Monitor project progress, identify bottlenecks, and implement corrective actions to ensure timely delivery of high-quality solutions.

- Drive the development and enhancement of analytical products and solutions for commercial and marketing analytics.

- Conduct market research and stay updated on industry trends, emerging technologies, and best practices.

- Collaborate with internal stakeholders, including data scientists, software developers, and domain experts, to define product requirements.

- Guide the product development lifecycle, from ideation and prototyping to testing, deployment, and maintenance.

- Design, Develop, and deploy complex and innovative analytical solutions for clients.

Research and Development (R&D) :

- Conduct ongoing research on statistical methodologies, data analytics techniques, and emerging trends in the pharmaceutical analytics domain.

- Evaluate the feasibility and applicability of new statistical models, algorithms, and AI/ML approaches.

- Collaborate with the R&D team to design and conduct experiments, analyze results, and propose innovative solutions.

- Translate research findings into actionable insights and contribute to thought leadership through publications, white papers, or conference presentations.