Hiring.Camp

Associate Director, Analytics Automation & Reusability

Novartis

·

1 week ago

Salary
$176k – $328k
Location
Remote Position (USA), United States of America
Workplace
Remote
Type
Full-time
Seniority
Entry
Experience
8+ years
Education
Bachelor
Source
Workday

Description

Band

Level 5


 

Job Description Summary

#LI-Remote

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 can be based remotely anywhere in the U.S. (there may be some restrictions based on legal entity). Please note that this role would not provide relocation as a result. The expectation of working hours and travel (domestic and/or international) will be defined by the hiring manager. This position will require 20% travel.


 

Job Description

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.


 

EEO Statement:

The Novartis Group of Companies are Equal Opportunity Employers. We do not discriminate in recruitment, hiring, training, promotion or other employment practices for reasons of race, color, religion, gender, national origin, age, sexual orientation, gender identity or expression, marital or veteran status, disability, or any other legally protected status. We strive to create an inclusive workplace that cultivates bold innovation through collaboration and empowers our people to unleash their full potential.


 

Accessibility and reasonable accommodations

The Novartis Group of Companies are committed to working with and providing reasonable accommodation to individuals with disabilities. If, because of a medical condition or disability, you need a reasonable accommodation for any part of the application process, or in order to perform the essential functions of a position, please send an e-mail to [email protected] call +1 (877)395-2339 and let us know the nature of your request and your contact information. Please include the job requisition number in your message.

https://www.novartis.com/careers/careers-research/notice-all-applicants-us-job-openings



 

Salary Range

$176,400.00 - $327,600.00


 

Skills Desired

Artificial Intelligence (AI), Biostatistics, Business Value Creation, Change Management, Curious Mindset, Data Governance, Data Literacy, Data Quality, Data Science, Data Visualization, Deep Learning, Graph Algorithms, Learning Agility, Machine Learning (ML), Machine Learning Algorithms, Nlp (Neuro-Linguistic Programming) And Genai (Inactive), Organization Awareness (Inactive), Pandas (Python) (Inactive), Python (Programming Language), R Programming, Stakeholder Engagement, Statistical Analysis, Structured Query Language (SQL), Time Series Analysis

Skills

PythonAzureJenkinsCI/CDSQLMachine LearningDeep LearningPandasAirflowData ScienceData EngineeringGitHubChange Management

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