Associate Director, Analytics Automation, Reusability

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🕒 July 20

🇺🇸 United States – Remote

💵 $176.4k - $327.6k / year

⏰ Full Time

🟠 Senior

👔 Director

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Novartis

WebsiteLinkedInAll Job Openings

10,000+ employees

Founded 1996

🏥 Healthcare

💼 Consulting

🏭 Manufacturing

Healthcare • Consulting • Manufacturing

Novartis is an innovative medicines company dedicated to reimagining medicine to improve and extend people’s lives. With a presence in over 250 million patients worldwide, Novartis focuses on harnessing scientific breakthroughs to develop transformative, high-value treatments in areas such as cardiovascular, renal and metabolic diseases, immunology, neuroscience, and oncology. The company is committed to diversity, equity, and inclusion, and aims to create a positive impact through societal contributions and environmental sustainability efforts. Furthermore, Novartis engages in research collaborations and embraces modern technology platforms to advance their research and development capabilities, making them a leader in the global healthcare industry.

📋 Description

• 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

🎯 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

🏖️ Benefits

• health, life and disability benefits • 401(k) with company contribution and match • a variety of other benefits • generous time off package including vacation, personal days, holidays and other leaves