Match Score
Against your primary resumeLogin to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Protocol Intelligence
Data-driven signals on your job's competitivenessTier-1 employer, mid-level generalist analytics role, metro location and broad dataset requirements drive high competition.
Requires pharma-specific claims, EHR and US-market dataset experience, making cross-industry transferability limited.
Explicit 4–6 years requirement plus mandatory pharma claims datasets and SQL/Snowflake/PowerBI skills increase strictness.
Job Description
Structured overview of role & requirementsAbout This Role
Lead end-to-end brand performance analytics including TRx/NRx analysis, competitive landscape, and market trends for new and inline pharma brands.
Develop advanced segmentation frameworks (HCP, patient, population) and analytics frameworks to support senior leadership decision-making and launch readiness.
Own patient journey analytics and develop frameworks to identify treatment gaps and barriers impacting brand growth.
Minimum Requirements
4-6 years of relevant experience in Pharma Commercial Analytics.
Bachelor’s or master’s degree in Information Science, Operations, Management, Statistics, Decision Sciences, Engineering, Life Sciences, Business Analytics, or related field.
Expertise in SQL, Snowflake, advanced Excel, PowerPoint; experience with US market pharma datasets (APLD, LAAD, EMR, etc.). Python and Power BI are desirable but not mandatory.
Not explicitly mentioned: Work Experience Required beyond stated range; Notice period; strict location beyond Hyderabad; regulatory constraints.
Ideal Candidate Profile
Experienced professional capable of handling multiple analytics projects simultaneously in a pharma commercial environment focused on US datasets.
Strategic thinker with problem-solving aptitude able to synthesize complex data into actionable insights influencing leadership decisions.
Proven ability to coordinate cross-functional teams and global stakeholders to drive timely delivery and quality in analytics projects.
