Google Data Analytics

#LI-Hybrid This role is responsible for building the tools, frameworks, and accelerators that enable the organization to scale AI, ML, and data science capabilities efficiently through automation and reusability. By transforming manual, one-off analytics into automated, production-grade solutions that can be reused across multiple use cases, this leader dramatically increases the speed and consistency of analytics delivery while reducing technical debt and enabling citizen data scientists to leverage enterprise-grade. This position will be located at the East Hanover site and will not have the ability to be located remotely. This position will require 20% travel as defined by the business (domestic and/ or international)., * 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., Power BI Refining Cannabis AWS Glue Pipelines Operations Automation Mentorship Governance Scalability Data Mining Data Quality Data Science Communication Data Analysis Data Modeling Data Wrangling Data Pipelines Responsible AI Data Governance Data Extraction Query Languages Report Creation Data Enrichment Computer Science Machine Learning Behavioral Health Advanced Analytics Data Visualization Workflow Management Amazon Web Services Feature Engineering Lifecycle Management Emerging Technologies Artificial Intelligence Microsoft Power Automate Permanent Resident Cards SQL (Programming Language) Robotic Process Automation Code Of Federal Regulations Extract Transform Load (ETL) Python (Programming Language) Retrieval Augmented Generation Business Intelligence Reporting Data Analysis Expressions (DAX) Generative Artificial Intelligence Automation Anywhere (RPA Software) MLOps (Machine Learning Operations) SQL Server Integration Services (SSIS) Tableau (Business Intelligence Software) +0

Github MLflow Jenkins Equities Kubeflow Dashboard Templates Pipelines Automation Innovation Statistics Forecasting Unit Testing Data Science Communication AWS SageMaker Technical Debt Apache Airflow Pharmaceuticals Test Automation Problem Solving Computer Science Machine Learning Systems Thinking Model Validation Data Engineering Azure Data Factory Regression Testing Scalability Design Technical Projects Workflow Management Workflow Automation Feature Engineering Software Engineering Resource Utilization Artificial Intelligence Software Quality (SQA/SQC) MLOps (Machine Learning Operations), * 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., MLflow Jenkins Equities Kubeflow Dashboard Templates Pipelines Automation Innovation Statistics Forecasting Unit Testing Data Science Communication AWS SageMaker Technical Debt Apache Airflow Pharmaceuticals Test Automation Problem Solving Computer Science Machine Learning Systems Thinking Model Validation Data Engineering Azure Data Factory Regression Testing Scalability Design Technical Projects Workflow Management Workflow Automation Feature Engineering Software Engineering Resource Utilization Artificial Intelligence Software Quality (SQA/SQC) MLOps (Machine Learning Operations) +0

Google Business Intelligence

Google IT Automation with Python

The salary for this position is expected to range between $145,600 and $270,400 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