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As the Data Scientist at Amgen, you will be responsible for developing and deploying advanced machine learning, operational research, semantic analysis, and statistical methods to uncover structure in large data sets. This role involves creating analytics solutions to address customer needs and opportunities.
Job Responsibility:
Accountable to drive full lifecycle of Data Science projects delivery and ability to guide data scientists in shaping the developing the solution and act as a subject matter expert in solving development and commercial questions
Assume the role of business owner and manage the Proprietary AI engine built to optimize Copay
Support Amgen Gross to Net and other V&A Transformation initiatives
Ensure models are trained with the latest data and meet the SLA expectations
Manage AI tool’s road map, working with a global cross functional team
Work in technical teams in development, deployment, and application of applied analytics, predictive analytics, and prescriptive analytics
Utilize technical skills such as hypothesis testing, machine learning and retrieval processes to apply 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
Model/analytics experiment and development pipeline leveraging MLOps
Oversee efforts of 1-3 associates, including setting performance standards, managing their staffing, and monitoring performance
Collaborate with technical teams to translate the business needs into technical specifications, particularly focusing on AI-driven automation and insights
Develop and integrate custom applications, intelligent dashboards, and automated workflows that incorporate AI capabilities to enhance decision-making and efficiency
Requirements:
Master’s degree in computer science, statistics or STEM majors with a minimum of 5 years of Information Systems experience
Bachelor’s degree in computer science, statistics or STEM majors with a minimum of 7 years of Information Systems experience
Foundational understanding of US pharmaceutical ecosystem and Patient support services offerings (Copay) and other standard data sets including claims, prescription
Experience with one or more analytic software tools or languages like R and Python
Strong foundation in machine learning algorithms and techniques
Experience in statistical techniques and hypothesis testing, experience with 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)
Outstanding analytical and problem-solving skills
Ability to learn quickly
Excellent communication and interpersonal skills
Experience with data engineering and pipeline development
Knowledge of NLP techniques for text analysis and sentiment analysis
Experience in analyzing time-series data for forecasting and trend analysis
Experience with AWS, Azure, or Google Cloud
Experience with Databricks platform for data analytics and MLOps
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