Data Scientist

• Develop and deploy advanced machine learning, operational research, semantic analysis, and statistical methods to uncover structure in large data sets
• Create analytics solutions to address customer needs and opportunities
• Work on upgrades and manage the execution of Proprietary AI engine built to optimize Copay and other GTN initiatives
• Ensure models are trained with the latest data and meet the 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 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
• 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

• Master’s degree and 1 to 3 years of computer science, statistics or STEM majors with a minimum of 1 year of Information Systems experience
• Bachelor’s degree and 3 to 5 years of computer science, statistics or STEM majors with a minimum of 2 years of Information Systems experience
• Diploma and 7 to 9 years of computer science, statistics or STEM majors with a minimum of 2 years of Information Systems experience
• Experience with one or more analytic software tools or languages like R and Python
• Foundational understanding of US pharmaceutical ecosystem and Patient support services offerings (Copay) and other standard data sets including claims, prescription
• Strong foundation in machine learning algorithms and techniques
• Experience in statistical techniques and hypothesis testing, experience with regression analysis, clustering and classification

• 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
• Any AWS Developer certification
• Any Python and ML certification
• Initiative to explore alternate technology and approaches to solving problems
• Skilled in breaking down problems, documenting problem statements, and estimating efforts
• Excellent analytical and troubleshooting skills
• Strong verbal and written communication skills
• Ability to work effectively with global, virtual teams
• High degree of initiative and self-motivation
• Ability to manage multiple priorities successfully
• Team-oriented, with a focus on achieving team goals

Competitive and comprehensive Total Rewards Plans that are aligned with local industry standards