Senior Manager, Pharma & Lifesciences Analytics – Value & Access Lead
Listed on 2026-01-06
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IT/Tech
Data Analyst, Data Science Manager
Senior Manager, Pharma & Lifesciences Analytics – Value & Access Lead (LIF
021642) is responsible for leading advanced analytics initiatives within pharmaceutical, value & access, and healthcare payer/provider domains. The role focuses on developing data‑driven strategies to support marketing, commercial excellence, and market access decisions across the U.S. market.
- Lead strategic analytics initiatives across pharmaceutical, Value&Access, and healthcare payer/provider domains.
- Apply machine learning techniques to structured and unstructured data to enhance patient stratification, drive sales and health outcomes.
- Develop analytical and statistical solutions to improve efficiency and drive innovations using Generative AI.
- Lead the development of U.S. market access strategies across therapeutic areas including formulary positioning, pricing, and reimbursement.
- Partner with global teams to align value messaging with regional payer and RAE/KAM expectations.
- Conduct and interpret advanced analytics to support decision‑making on promotional strategies and effectiveness (e.g., ROI, A/B testing, campaign performance).
- Lead the Health System engagement by generating valuable insights for RAE/KAM teams.
- Handle complex statistical analysis to measure the effectiveness of certain campaigns and help in monitoring VCOs/KAM/NAD/NAM performance.
- Leverage data analytics tools to analyze market trends, track sales performance, and provide actionable insights to sales teams.
- Design and execute test‑control methodologies and statistical procedures to evaluate marketing campaign success.
- Lead predictive analytics projects including segmentation, profiling, and targeting strategies.
- Functionally and directionally lead an offshore analytics team while maintaining individual‑contributor responsibilities.
- Act as a strategic consultant to stakeholders, translating business needs into analytical solutions and actionable insights.
- Collaborate with data engineering and source data teams to address data quality and timing issues.
- Bachelor’s in Pharma/Technology/BE.
- Experience in U.S. healthcare analytics, including pharmaceuticals, biotech, or payer/provider systems.
- Machine learning and statistical modeling knowledge (e.g., XGBoost, Random Forest, NLP, deep learning).
- Knowledge of GenAI.
- Proficient in Python, SQL.
- Strong knowledge of U.S. healthcare datasets:
Medicare/Medicaid, commercial claims, EMR systems, sales & commercial data sets in healthcare, etc. - Solid grasp of healthcare economics, policy frameworks, and regulatory constraints.
- Knowledge of Spark, and data visualization tools (Power BI, Tableau) and R is preferred.
- Strong analytical, problem‑solving skills, and technical aptitude.
- Expert verbal and written communication skills.
- High degree of energy & execution and client‑connect experience is a “Must.”
- Ability to work in a global environment.
- Proven work experience as a team leader or supervisor.
- Good analytical and problem‑solving skills.
- Good interpersonal skills.
- Lead AI‑first transformation – build and scale AI solutions that redefine industries.
- Make an impact – drive change for global enterprises and solve business challenges that matter.
- Accelerate your career – gain hands‑on experience, world‑class training, mentorship, and AI certifications to advance your skills.
- Grow with the best – learn from top engineers, data scientists, and AI experts in a dynamic, fast‑moving workplace.
- Committed to ethical AI – work in an environment where governance, transparency, and security are at the core of everything we build.
- Thrive in a values‑driven culture – our courage, curiosity, and incisiveness, built on a foundation of integrity and inclusion, allow your ideas to fuel progress.
The approximate annual base compensation range for this position is [$130,000 to $160,000]. The actual offer, reflecting the total compensation package plus benefits, will be determined by a number of factors which include but are not limited to the applicant’s experience, knowledge, skills, and abilities; geographic location; and internal equity.
Los Angeles, California based candidates are not…
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