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About This Role
JOB TITLE: Vice President of AI, Data & Analytics
DEPARTMENT: Information Technology
REPORTS TO: Chief Information Officer
CLASIFICATION: Exempt
SALARY: $160,000 – $165,000 per year
DATE: January 2026
POSITION OVERVIEW
The Vice President of AI, Data & Analytics is responsible for setting and executing the enterprise strategy for data, analytics, and artificial intelligence to enable insight-driven decision-making, operational excellence, and responsible innovation across the organization. This role serves as a senior technology leader and strategic partner to executive leadership.
ESSENTIAL FUNCTIONS
- Define and lead the AI, Data & Analytics team with a focus on enterprise data, analytics, and AI strategy aligned to organizational priorities
- Own enterprise data architecture, including data ingestion, storage, modeling, analytics, and semantic layers
- Lead the development and deployment of advanced analytics, machine learning, and AI solutions, including GenAI where appropriate
- Establish and enforce data governance, data quality standards, stewardship models, and metadata management
- Create and oversee responsible AI and AI governance frameworks, including model risk management and ethical use guidelines
- Partner with Information Security, Legal, and Compliance to ensure privacy-by-design, data protection, and regulatory alignment
- Build, mentor, and scale high-performing data engineering, analytics, and data science teams
- Manage budgets, vendors, and strategic partners related to data and AI platforms
- Measure, communicate, and continuously improve the business value and ROI of data and AI initiatives
SKILLS REQUIREMENT
- Deep expertise in machine learning algorithms and data modelling.
- Exceptional leadership, people management and communication abilities.
- Strong strategic vision and the ability to translate it into actionable plans.
- Sound judgment regarding ethics, privacy and bias in data and AI.
- Ability to liaise effectively between technical teams and non-technical stakeholders.
QUALIFICATIONS/SKILLS REQUIREMENT
- 10+ years in technology and data-related roles, with at least 7 years leading AI, analytics or data science organizations.
- Advanced degree (MS or PhD) in Computer Science, Data Science, Statistics, Mathematics or a related field
- Proven track record of deploying enterprise-scale AI/ML solutions that drive measurable business outcomes.
- Experience across diverse industries enabling you to apply best practices from technology, finance, healthcare, retail, manufacturing and others.
- Strong understanding of data governance, architecture, infrastructure and modern data platforms (Spark, cloud data warehouses).
VOLUNTEER REQUIREMENT
- Participates in the Annual 5K Fundraiser and September 11th Commemoration, as assigned.
- Assists with other special projects and events in support of all 9/11 Memorial and Museum, as assigned.
The National September 11 Memorial & Museum (9/11 Memorial & Museum) is an equal opportunity employer. Applicants who meet the qualification requirements of the role will receive consideration without regard to their race, color, religion, sex, sexual orientation, age, national origin, disability, status as a protected veteran, or any other characteristic protected by applicable law. The 9/11 Memorial & Museum endeavors to make reasonable accommodations for applicants with disabilities and other accommodation needs under applicable law. If you are an individual with a legally recognized accommodation need and require assistance during the application process, please contact Ronni Cantor at careers@911memorial.org with your specific accommodation request.
The 9/11 Memorial & Museum is committed to an organizational culture that supports and reinforces our institutional values including our commitment to inclusive representation. We are committed to reflecting the unique experiences of the nearly 3,000 victims who were killed indiscriminately in the 1993 and 2001 terrorist attacks and the wider communities impacted in lower Manhattan, at the Pentagon, and near Shanksville, PA.
Salary Context
This $160K-$165K range is below the median for AI/ML Engineer roles in our dataset (median: $170K across 217 roles with salary data).
View full AI/ML Engineer salary data →Role Details
About This Role
AI/ML Engineers build and deploy machine learning models in production. They work across the full ML lifecycle: data pipelines, model training, evaluation, and serving infrastructure. The role has evolved significantly over the past two years. Where ML Engineers once spent most of their time on model architecture, the job now tilts heavily toward inference optimization, cost management, and integrating LLM capabilities into existing systems. Companies want engineers who can ship production systems, and the experimenter-only role is fading fast.
Day-to-day, you're writing training pipelines, debugging data quality issues, setting up evaluation frameworks, and figuring out why your model performs differently in staging than it did on your dev set. The best ML engineers are obsessive about reproducibility and measurement. They instrument everything. They know that a model is only as good as the data feeding it and the infrastructure serving it.
Across the 37,339 AI roles we're tracking, AI/ML Engineer positions make up 91% of the market. At The National September 11 Memorial & Museum, this role fits into their broader AI and engineering organization.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
What the Work Looks Like
A typical week might include: debugging a data pipeline that's silently dropping 3% of training examples, running A/B tests on a new model version, writing documentation for a feature flag system that lets you roll back model deployments, and reviewing a junior engineer's PR for a new evaluation metric. Meetings tend to be cross-functional since ML touches product, engineering, and data teams.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
Skills Required
Python and PyTorch dominate the requirements. Most roles expect experience with cloud platforms (AWS, GCP, or Azure) and familiarity with ML frameworks like TensorFlow or JAX. RAG (Retrieval-Augmented Generation) has become a top-3 skill requirement as companies integrate LLMs into their products. Docker and Kubernetes show up in about a third of postings, reflecting the production focus of the role.
Beyond the core stack, employers increasingly want experience with experiment tracking tools (MLflow, Weights & Biases), feature stores, and vector databases. Fine-tuning experience is valuable but less common than you'd think from reading Twitter. Most production LLM work is RAG and prompt engineering, not fine-tuning. If you have both, you're in a strong position.
Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
Compensation Benchmarks
AI/ML Engineer roles pay a median of $154,000 based on 8,743 positions with disclosed compensation. This role's midpoint ($162K) sits 6% above the category median. Disclosed range: $160K to $165K.
Across all AI roles, the market median is $190,000. Top-quartile compensation starts at $244,000. The 90th percentile reaches $300,688. For comparison, the highest-paying categories include AI Engineering Manager ($293,500) and AI Safety ($274,200). By seniority level: Entry: $85,000; Mid: $147,000; Senior: $225,000; Director: $230,600; VP: $248,357.
The National September 11 Memorial & Museum AI Hiring
The National September 11 Memorial & Museum has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in New York, NY, US. Compensation range: $165K - $165K.
Location Context
AI roles in New York pay a median of $204,100 across 1,633 tracked positions. That's 7% above the national median.
Career Path
Common paths into AI/ML Engineer roles include Data Scientist, Software Engineer, Research Engineer.
From here, career progression typically leads toward ML Architect, AI Engineering Manager, Principal ML Engineer.
The fastest path into ML engineering is through software engineering with a self-directed ML education. A CS degree helps, but production engineering skills matter more than academic credentials. Build something that works, deploy it, and measure it. That portfolio project is worth more than a Coursera certificate. For career growth, the fork comes around the senior level: go deep on technical complexity (staff/principal track) or move into managing ML teams.
What to Expect in Interviews
Expect system design questions around ML pipelines: how you'd build a training pipeline for a specific use case, handle data drift, or design A/B testing infrastructure for model deployments. Coding rounds typically involve Python, with emphasis on data manipulation (pandas, numpy) and algorithm implementation. Take-home assignments often ask you to build an end-to-end ML pipeline from raw data to deployed model.
When evaluating opportunities: Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
AI Hiring Overview
The AI job market has 37,339 open positions tracked in our dataset. By seniority: 3,672 entry-level, 23,272 mid-level, 7,048 senior, and 3,347 leadership roles (Director, VP, C-Level). Remote roles make up 7% of the market (2,732 positions). The remaining 34,484 roles require on-site or hybrid attendance.
The market median for AI roles is $190,000. Top-quartile compensation starts at $244,000. The 90th percentile reaches $300,688. Highest-paying categories: AI Engineering Manager ($293,500 median, 21 roles); AI Safety ($274,200 median, 24 roles); Research Engineer ($260,000 median, 264 roles).
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
The AI Job Market Today
The AI job market spans 37,339 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (33,926), AI Software Engineer (823), AI Product Manager (805). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (3,672) are outnumbered by mid-level (23,272) and senior (7,048) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 3,347 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 7% of all AI roles (2,732 positions), with 34,484 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $190,000. Top-quartile roles start at $244,000, and the 90th percentile reaches $300,688. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Engineering Manager roles lead at $293,500 median, while Prompt Engineer roles sit at $145,600. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Rag (23,721 postings), Aws (12,486 postings), Rust (10,785 postings), Python (5,564 postings), Azure (3,616 postings), Gcp (3,032 postings), Prompt Engineering (2,112 postings), Kubernetes (1,713 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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