Data Scientist

Amgen is seeking a Senior Associate Data Scientist to join our Value & Access Insights team in Hyderabad/Secunderabad, Telangana, India. In this pivotal role, you will leverage advanced machine learning, operational research, semantic analysis, and statistical methods to analyze large datasets and develop innovative analytics solutions that address critical customer needs within the US pharmaceutical ecosystem. You will be instrumental in optimizing Copay and other Gross-to-Net (GTN) initiatives by managing and upgrading our proprietary AI engine, ensuring model accuracy with the latest data, and meeting stringent Service Level Agreements (SLAs). This position requires acting as a subject matter expert to resolve development and commercial challenges, collaborating with a global cross-functional team on the AI tool's roadmap, and contributing to the development, deployment, and application of predictive and prescriptive analytics.

Your responsibilities will include utilizing technical skills in hypothesis testing, machine learning, and retrieval processes to identify trends and analyze relevant information. You will perform exploratory and targeted data analyses, develop and manage model/analytics experiment pipelines using MLOps principles, and translate business needs into technical specifications, with a focus on AI-driven automation and insights. Furthermore, you will develop and integrate custom applications, intelligent dashboards, and automated workflows incorporating AI capabilities to enhance decision-making and operational efficiency.

We are looking for candidates with a strong foundation in machine learning algorithms, statistical techniques, and hypothesis testing, including regression, clustering, and classification. Proficiency in R or Python is essential, along with a foundational understanding of the US pharmaceutical ecosystem, patient support services (like Copay), and common data sets such as claims and prescription data. Experience with MLOps practices and tools (e.g., MLflow, Kubeflow, Airflow), DevOps tools (e.g., Docker, Kubernetes, CI/CD), and cloud platforms (AWS, Azure, GCP) are highly desirable. Familiarity with NLP techniques, time-series analysis, Databricks, and libraries like TensorFlow, PyTorch, and Scikit-learn will be advantageous. Excellent analytical, problem-solving, communication, and collaboration skills are crucial for success in this role.

Basic Qualifications include a Master's degree in Computer Science, Statistics, or a STEM major with a minimum of 2 years of Information Systems experience, or a Bachelor's degree in Computer Science, Statistics, or a STEM major with a minimum of 4 years of Information Systems experience. Preferred certifications include any AWS Developer or Python and ML certification.