Senior Data Scientist - Safety Analytics & Signal Detection

Amgen Inc; Hyderabad; On-site; INR 2,000,000 - 3,200,000; Full time

Job summary

Amgen Inc in Hyderabad, India, seeks a Senior Data Scientist to apply advanced statistics and data science to pharmacovigilance, safety signal detection, and post‑marketing surveillance within Global Patient Safety. You will design analyses using internal safety data, spontaneous reports, and real‑world data to support data‑driven safety decisions.

The role emphasizes frequentist and Bayesian methods, temporal analyses, ML/NLP approaches, reproducible workflows, and clear communication of

Qualifications

• Strong background in statistics and complex statistical analysis.
• Proficiency in 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.
• Ability to operate effectively in a matrixed environment.

Responsibilities

• Provide data science and statistical support for safety surveillance and signal assessment.
• Partner with cross-functional teams to develop analytical approaches for safety questions.
• Apply frequentist, Bayesian, temporal, and other methods used in pharmacovigilance.
• Analyze internal safety data, spontaneous reports, and real‑world data to generate insights.
• Develop reproducible analytical workflows using programming, automation, and visualization.
• Evaluate advanced analytics, ML, NLP, and AI approaches to support safety surveillance.
• Communicate methods and findings clearly to stakeholders.

Skills

Statistics

Python/R/SQL/SAS

Machine Learning/AI

Communication

Leadership

Project management

Cross-functional collaboration

Education

Doctorate in a quantitative field

Masters in quantitative field

Bachelors in quantitative field

Associate degree with experience

Tools

Python

R

SQL

SAS

Job 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
• Masters degree and 6 years of Data Science / Statistics / Biostatistics / Epidemiology / Mathematics / or related quantitative experience; OR
• Bachelors degree and 8 years of Data Science / Statistics / Biostatistics / Epidemiology / Mathematics / or related quantitative experience; OR
• Associates degree and 10 years of Data Science / Statistics / Biostatistics / Epidemiology / Mathematics / or related quantitative experience;

Education Experience (Preferred)

• 8+ 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, R, SQL, SAS, or comparable analytical technologies
• 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