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.(ref : hirist.tech)