Senior Data Scientist - Safety Analytics & Signal Detection
Hyderabad Full-time Senior AI Research
At a glance
Senior AI Research role at Amgen. Hyderabad · full-time.
Pay not stated AI Research salary
RoleAI Research
SenioritySenior
LocationHyderabad
EmploymentFull-time
PostedSep 1, 2026 · 7w ago
Role brief
aimlroles summary, based on the employer's posting.
What you'll do
- Analyze safety records, spontaneous reports and real-world data to surface findings for surveillance and signal assessment
- Shape analyses for safety questions and post-marketing monitoring alongside therapeutic-area safety and signal-management teams
- Select suitable statistical approaches, including frequentist, Bayesian and time-based methods, for safety signal detection
- Create repeatable analytical workflows through coding, automation and visualization
- Present methods, findings, limitations and recommendations clearly to technical and non-technical stakeholders
What you bring
- You meet one route: a doctorate with two years, a master’s with six, or another listed degree-and-experience path
- You have strong statistical skills and can use Python, R, SQL or SAS for analysis
- You understand machine learning and newer AI approaches
- You communicate well, influence cross-functional teams and manage several priorities
Who this fits
This role suits a senior quantitative practitioner focused on pharmacovigilance, safety signals and post-marketing analysis. Pharmaceutical or regulated healthcare experience, plus familiarity with safety data and signal detection, is preferred.
From the employer
Career Category
SafetyJob Description
Group Purpose
Integrated Signal Management group is responsible for the direction and strategy for safety signal detection and management, safety governance, and quality complaints trending and analytics. It drives policies, research, innovation, and implementation of best practices in safety data mining, statistical signal detection, signal management and tracking, product complaint trending and analytics, risk management, benefit-risk assessment, and safety communications.
Job Summary
The Senior Data Scientist applies advanced expertise in statistics, data science, and analytical methodologies to support pharmacovigilance, safety signal detection, post-marketing surveillance, and safety decision-making within Global Patient Safety. The role works closely with Therapeutic Area Safety, Integrated Signal Management, and cross-functional partners to design and execute complex analyses using internal safety data, spontaneous reporting systems, real-world data, and other safety-relevant data sources.
This role applies and evaluates a range of analytical approaches including frequentist and Bayesian signal detection methods, temporal and trending analyses, observational data methods, and emerging machine learning and artificial intelligence techniques. The role is responsible for translating complex safety questions into appropriate analytical designs, developing reproducible and scalable analytical workflows, evaluating methodological assumptions and limitations, and communicating scientifically defensible findings to technical and non-technical stakeholders.
Through the application of advanced analytics, automation, visualization, and innovative data science methods, the Senior Data Scientist helps strengthen Amgen's safety surveillance capabilities, improve analytical efficiency, and enable timely, data-driven decisions that support patient safety.
Key Activities
1. Provides data science and statistical support for safety surveillance, signal detection, and signal assessment activities.
2. Partners with TA Safety and Integrated Signal Management to develop and execute analytical approaches for safety questions and post-marketing surveillance.
3. Applies frequentist, Bayesian, temporal, and other fit-for-purpose statistical methods used in pharmacovigilance.
4. Analyzes internal safety data, spontaneous reporting data, real-world data, and other relevant sources to generate actionable insights.
5. Develops reproducible analytical workflows using programming, automation, and visualization technologies.
6. Evaluates and applies advanced analytics, machine learning, NLP, and AI-enabled approaches to support safety surveillance and analytical efficiency.
7. Communicates analytical methods, findings, limitations, and recommendations clearly to cross-functional stakeholders.
Knowledge and Skills
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.
Preferred
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
Education (Basic)
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;
Education & Experience (Preferred)
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