Band

Level 6

 

Job Description Summary

#LI-Remote

Novartis has an exciting opportunity for a Director, Analytics Standards & Impact Measurement. This role is responsible for establishing enterprise-wide standards for advanced AI, ML, and data science rigor, defining measurement frameworks, and quantifying the business impact of all analytics and AI initiatives across Commercial Analytics. By ensuring that analytics outputs, whether built by expert data scientists or citizen data scientists using self-serve platforms, meet the highest standards of AI/ML validity, regulatory compliance, and business value, this director enables democratized, trustworthy analytics at scale while measuring and communicating the return on analytics investments.

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

• Define enterprise-wide AI, ML, and data science standards embedded into self-serve analytics platforms, ensuring citizen data scientists follow rigorous methodologies automatically.
• Establish model validation protocols, testing frameworks, and quality gates built into automated workflows for predictive models and AI solutions.
• Create standardized methodologies for common use cases (patient predictive models, HCP targeting, driver analysis) that can be templatized for citizen data scientists.
• Define enterprise-wide frameworks for measuring analytics impact including lift analysis, ROI calculation, incrementality measurement, and business value assessment.
• Execute enterprise-level impact measurement studies to quantify business value of analytics initiatives and report quarterly/annual ROI to leadership.
• Establish production-readiness criteria for AI/ML models from self-serve platforms, including quality thresholds, documentation requirements, and approval workflows.
• Ensure all AI, ML, and data science outputs meet regulatory requirements ( HIPAA, GDPR, promotional review) and partner with Legal, ERC, and Medical Affairs on governance.
• Monitor outputs from self-serve platforms, conduct model audits, and provide feedback to platform teams on quality improvements.

Essential Requirements

• Advanced degree in Data Science, Machine Learning, Statistics, or related quantitative field; or bachelor’s degree with 10+ years relevant experience.
• 10+ years of experience in data science, machine learning, advanced analytics, or AI development.
• 5+ years of leadership experience setting AI/ML standards and measuring impact in commercial pharma or healthcare.
• Expert knowledge of advanced analytics methodologies: machine learning, causal inference, experimental design, predictive modeling, AI validation.
• Deep knowledge of pharmaceutical analytics and regulatory environment for AI/ML applications.
• Proficiency in data science/AI programming and AI/ML platforms.
• Proven ability to influence without direct authority and drive adoption of AI/ML standards across diverse teams.
• Exceptional communication skills; ability to translate complex AI/ML concepts for business audiences and executives.

Preferred Qualities

• Experience with self-serve analytics and AI platforms and embedding governance into automated workflows.
• Strong business acumen with ability to measure and communicate ROI of AI/ML initiatives to C-suite.
• Systems thinker who can balance AI/ML rigor with practical business needs and timelines.
• Experience building communities of practice and enabling citizen data scientists in AI/ML development.

The salary for this position is expected to range between $194,600 and $361,400 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

 

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

$194,600.00 - $361,400.00

 

Skills Desired

Agile (Programming Methodology) (Inactive), Artificial Intelligence (AI), Business Value Creation, Change Management, Curious Mindset, Data Governance, Data Literacy, Data Quality, Data Science, Data Strategies, Data Visualization, Deep Learning, Learning Agility, Machine Learning (ML), Machine Learning Algorithms, Mentorship, Nlp (Neuro-Linguistic Programming) And Genai (Inactive), Organization Awareness (Inactive), Stakeholder Engagement, Statistical Analysis, Time Series Analysis, Vision (Inactive)