About the role
- Strong background in statistics and complex statistical analysis.
- Proficiency in one or more analytical programming languages such as Python, R, SQL, or SAS
- Working knowledge of machine learning and emerging AI methods
- Strong communication skills.
- Ability to lead/influence cross-functional teams.
- Ability to manage multiple projects and priorities simultaneously.
- Ability to operate effectively in a cross-functional, matrixed environment.
- Knowledge of pharmacovigilance principles, safety signal detection, signal management, and post-marketing surveillance.
- Familiarity with pharmacovigilance and safety data sources, including spontaneous reporting systems, safety databases, and real-world data sources.
- Knowledge of frequentist and Bayesian statistical approaches used in safety surveillance and signal detection
- Doctorate degree and 2 years of Data Science / Statistics / Biostatistics / Epidemiology / Mathematics / or related quantitative experience; OR
- Master’s degree and 6 years of Data Science / Statistics / Biostatistics / Epidemiology / Mathematics / or related quantitative experience; OR
- Bachelor’s degree and 8 years of Data Science / Statistics / Biostatistics / Epidemiology / Mathematics / or related quantitative experience; OR
- Associate’s degree and 10 years of Data Science / Statistics / Biostatistics / Epidemiology / Mathematics / or related quantitative experience;
- 8-13 years of applied data science, statistics, analytics, or related quantitative experience
- Experience in pharmaceutical, biotechnology, pharmacovigilance, clinical safety, epidemiology, or another regulated healthcare environment
- Experience analyzing adverse event, spontaneous reporting, real-world, claims, EHR, or other healthcare data
- Experience with pharmacovigilance signal detection methodologies, including frequentist and/or Bayesian approaches
- Experience using Python OR SAS OR R and SQL or comparable analytical technologies hands with coding
- Experience with machine learning, NLP, or AI-enabled analytical methods is desirable
- Degree in Statistics, Biostatistics, Mathematics, Data Science, Epidemiology, Computer Science, Engineering, or another quantitative/scientific field