Key Responsibilities

• Design and implement workflow automation solutions for AI/ML and analytics processes (Airflow, dbt, Azure Data Factory).
• Build CI/CD pipelines for data science code, enabling automated testing, deployment, and monitoring of ML models.
• Design MLOps infrastructure to streamline the model development, validation, and deployment lifecycle.
• Build and maintain a library of reusable AI/ML components (feature engineering modules, model templates, prediction pipelines, visualization templates).
• Create standardized notebooks, scripts, and dashboards for common data science use cases that can be easily adapted for new projects.
• Build tools and platforms that enable business users and citizen data scientists to access AI/ML capabilities without engineering support.
• Implement automated testing frameworks for data science code (unit tests, integration tests, model validation tests, regression tests).
• Work with Infrastructure team to optimize performance and resource utilization of automated AI/ML solutions.

Essential Requirements:

• Advanced degree in Computer Science, Data Science, Statistics, or related field; or Bachelor's degree with 8+ years relevant experience.
• 8+ years of experience in analytics engineering, data engineering, or software engineering roles.
• 3+ years of experience leading technical projects or small teams.
• Experience with workflow orchestration tools (Airflow, Prefect, dbt) and CI/CD tools (GitHub Actions, Jenkins).
• Knowledge of MLOps principles and tools (MLflow, Kubeflow, SageMaker).
• Experience with testing frameworks and code quality tools.
• Excellent documentation and communication skills.

Desired Requirements:

• Experience in pharmaceutical, healthcare, or regulated industries.
• Background in both analytics/data science and software engineering best practices.
• Creative problem-solver who can identify opportunities for automation and reusability.
• Strong systems thinking with ability to design scalable, maintainable solutions.
• Experience building internal tools and platforms used by diverse user groups including citizen data scientists.

Novartis Compensation Summary:

The salary for this position is expected to range between $176,400 and $327,600 per year.

The final salary offered is determined based on factors like, but not limited to, relevant skills and experience, and upon joining Novartis will be reviewed periodically. Novartis may change the published salary range based on company and market factors.

Your compensation will include a performance-based cash incentive and, depending on the level of the role, eligibility to be considered for annual equity awards.

US-based eligible employees will receive a comprehensive benefits package that includes health, life and disability benefits, a 401(k) with company contribution and match, and a variety of other benefits. In addition, employees are eligible for a generous time off package including vacation, personal days, holidays and other leaves.

Why Novartis: Helping people with disease and their families takes more than innovative science. It takes a community of smart, passionate people like you. Collaborating, supporting and inspiring each other. Combining to achieve breakthroughs that change patients’ lives. Ready to create a brighter future together? https://www.novartis.com/about/strategy/people-and-culture

Benefits and Rewards: Learn about all the ways we’ll help you thrive personally and professionally.
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