Senior Manager, Real-World Oncology Analytics

Regeneron Pharmaceuticals, Inc (USA); Village of Sleepy Hollow (NY); Sur place; USD 151 000 - 246 000; Plein temps

Avantages offerts par ce poste

Annual bonuses

Equity awards

401(k) company match

Health and wellness programs

Résumé du poste

Regeneron Pharmaceuticals, Inc. in Sleepy Hollow, NY seeks a Senior Manager, Real-World Data and Analytics (RWDnA) to drive real-world evidence in oncology.

You will develop RWE queries and SAPs, perform hands-on programming, and coordinate with vendors to deliver analyses and publications. The role requires advanced degrees in quantitative fields and substantial experience with SAS/R, survival analysis, propensity scores, and ML methods on large healthcare data sources such as claims and EHRs.

Qualifications

• Doctoral or master's with substantial hands-on programming experience.
• Experience with real-world data sources and oncology research.
• Proficiency in statistical methods and machine learning approaches.

Responsabilités

• Develop RWE queries, protocols, and SAPs for oncology projects.
• Translate analytic findings to clear insights for project teams.
• Hands-on programming and QC of analytic code using real-world data assets.
• Evaluate data sources to address research questions.
• Contribute to scientific communications and collaborate with vendors/partners.

Connaissances

Real-world data experience

Scientific communication

Oncology research knowledge

Analytical thinking

Formation

Doctoral degree in quantitative field

Master's degree in related field

Outils

SAS

R

Description du poste

Regeneron Pharmaceuticals, Inc. in Sleepy Hollow, NY seeks a Senior Manager, Real-World Data and Analytics (RWDnA) to drive real-world evidence in oncology.

You will develop RWE queries and SAPs, perform hands-on programming, and coordinate with vendors to deliver analyses and publications. The role requires advanced degrees in quantitative fields and substantial experience with SAS/R, survival analysis, propensity scores, and ML methods on large healthcare data sources such as claims and EHRs.