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Specialized life-sciences analytics reduces applicants though mid-level data skills increase competition.
Role demands pharma commercialization analytics expertise, limiting cross-industry transferability.
Explicit 2–4 years, pharma analytics, AI/ML and specific tooling make filters strict.
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Provide advanced analytical support on complex projects for life sciences clients, ensuring high-quality delivery and client satisfaction.
Lead and manage the India-based delivery team, overseeing project execution, documentation, and communication.
Drive enhancement of services and deliverables while fostering internal and external relationships to support business growth and mentoring initiatives.
Graduate/Master’s degree from Tier-I/Tier-II institution in computer science, engineering, statistics or related field.
2-4 years of experience in data science with proven impact in pharmaceutical/life sciences industry.
Mandatory AI/ML experience; Gen AI experience is a plus.
Strong hands-on skills with analytics and visualization tools (Python, Alteryx, Tableau, PowerBI) and experience with cloud platforms (AWS, Azure, GCP).
Experienced in drug commercialization analytics such as sales force analytics, omnichannel, attribution modeling.
Demonstrated leadership and mentoring ability managing junior team members and driving delivery excellence.
Comfortable working in an international matrix environment collaborating with US clients during US working hours.