US V&A Insights - Data Scientist

Overview

Senior Associate Data Scientist at Amgen, developing and deploying advanced machine learning, operational research, semantic analysis and statistical methods to uncover structure in large data sets and build analytics solutions for customer needs.

What you'll do

• Work on upgrades and manage the execution of a proprietary AI engine built to optimize Copay and other GTN initiatives.
• Ensure models are trained with the latest data and meet SLA expectations.
• Act as a subject matter expert in solving development and commercial questions.
• Work with a global cross-functional team on the AI tool's road map.
• Work in technical teams on development, deployment and application of applied, predictive and prescriptive analytics.
• Apply hypothesis testing, machine learning and retrieval processes with statistical and data mining techniques to identify trends, create figures and analyze other relevant information.
• Perform exploratory and targeted data analyses using descriptive statistics and other methods.
• Develop the model and analytics experiment pipeline leveraging MLOps.
• Collaborate with technical teams to translate business needs into technical specifications, focusing on AI-driven automation and insights.
• Develop and integrate custom applications, intelligent dashboards and automated workflows that incorporate AI capabilities.

What you'll need

• Any degree in computer science, statistics or STEM majors with 5-9 years of Information Systems experience.
• Experience with one or more analytic software tools or languages such as R and Python.
• Foundational understanding of the US pharmaceutical ecosystem and patient support services offerings (Copay) and standard data sets including claims and prescription.
• Strong foundation in machine learning algorithms and techniques.
• Experience in statistical techniques and hypothesis testing, including regression analysis, clustering and classification.

Nice to have

• Experience in MLOps practices and tools (e.g., MLflow, Kubeflow, Airflow).
• Experience in DevOps tools (e.g., Docker, Kubernetes, CI/CD).
• Proficiency in Python and relevant ML libraries (e.g., TensorFlow, PyTorch, Scikit-learn).
• Experience with data engineering and pipeline development.
• Knowledge of NLP techniques for text analysis and sentiment analysis.
• Experience analyzing time-series data for forecasting and trend analysis.
• Experience with AWS, Azure or Google Cloud.
• Experience with the Databricks platform for data analytics and MLOps.
• Any AWS Developer certification (preferred).
• Any Python and ML certification (preferred).

Details

• Location: India - Hyderabad.