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About This Role
Senior Manager, People Analytics, Insights & AI Enablement
At CHANEL, we are focused on creating an inclusive culture that nurtures personal growth, contributing to collective progress. We believe the uniqueness of each individual increases the diversity, complementarity, and effectiveness of our teams. We strongly encourage your application, as we value the perspective, experience and potential you could bring to CHANEL.
About the role:
CHANEL is looking for a Senior Manager, People Analytics, Insights & AI Enablement to join our New York City team. This role sits in the Organizational Development & Effectiveness (OD&E) Center of Excellence within the US People & Organization (P&O/ Human Resources) team. You will enable P&O (HR) to make better, faster, evidence-based decisions through people analytics, insights and the thoughtful use of technology and AI. You will define P&O’s AI needs (in partnership with People Operations), how people insights and foresights are produced and used, and how AI supports the future P&O operating model. This role is a strategist and enabler who turns people data, insights, and AI into business outcomes and a future-fit org.
Minimum of 7 years' experience in People Analytics, Human Resources, Process Insights, with recent expertise in Artificial Intelligence. Hands on experience in Microsoft environment with Power BI, AI Tools, Qualtrics- Employee Survey, etc.
What impact you can create at CHANEL:
- Define the people analytics roadmap and standard dashboards to support people insights across the US— so the same questions are answered the same way, reducing fragmented one-off demand and freeing the team for higher-value, predictive work
- Translate workforce data into insights and recommended actions, and build predictive, forward-looking models for workforce planning (e.g., retention, capacity, and scenario forecasting)
- Define P&O technology strategy, innovation, and AI use-case framing — how the team uses, evaluates, and rolls out AI tools to support the future operating model
- Identify augment-vs.-automate workflows, serve as part of the local and global AI ambassador community, and guide responsible, human-centered AI use within P&O, grounded in the value the work is trying to create — establishing guardrails and scaling adoption through repeatable standards rather than one-off experimentation
- Drive AI adoption in P&O by connecting new tools to the team’s day-to-day problems and assess P&O’s AI maturity and readiness
- Enable self-service analytics for HRBPs and business leaders — with the right guardrails and advance data literacy across P&O
- Own employee listening and our employee engagement survey (Voices) analytics — turning what people tell us into insight
Partner with People Operations to improve data quality and data governance in service of AI integration
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You are energized by:
- Turning data into decisions — and data storytelling that moves leaders to act
- Building a data-driven, insight-led culture and raising data literacy across the function
- Future-of-work thinking and responsible, human-centered use of AI
- Building capability and insight, not just producing dashboards and reports
- Working across People Operations, Tech, HRBPs, COEs, POLT, the broader P&O team, and Global
Standardizing where it creates capacity, and customizing where it creates real value
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What you will bring to the team:
- Analytics, insights, and data-storytelling depth — this role if not a reporting analyst
- Hands-on analytics fluency with modern tooling (e.g., Power BI and AI-enabled platforms ), paired with the judgment to know what to standardize versus customize
- Hands-on experience leveraging AI to transform HR processes, including building AI agents and automations using Microsoft Power Automate or similar platforms, independently or in partnership with technology teams
- AI and technology enablement fluency, with a point of view on augment vs. automate, and a responsible, ethical approach to people with data — privacy and governance
- Brings practical AI implementation experience and best practices, with a proven track record of applying AI solutions in an HR environment
- Future-of-work thinking and a sense of where the function is heading
- Experience defining analytics, roadmaps and standard metrics, and partnering with People Operations / HRIS, Tech, and Finance on shared, trusted workforce data
- Senior Manager-level judgment, with the ability to influence senior stakeholders and to set scope and hold boundaries with People Operations, Tech, and Global
Comfort with a clear own / don’t-own line: this role owns US People Analytics strategy, P&O AI strategy and AI use-case framing, and employee listening (Voices) — it does not own Workday configuration and system implementation, enterprise IT architecture, security and governance decisions alone, the P&O Tech Roadmap’s final technology procurement decisions, or reporting standards
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What skills you will learn / experiences you might have:
- Stand up the analytics and AI engine of a newly formed Center of Excellence
- Shape how CHANEL US applies AI across P&O — with visibility to POLT and senior leadership
- Bridge Global reporting and US-specific business needs, building fluency across both
- Grow as a people-analytics and AI strategist at the frontier of how P&O creates value
Position Logistics:
- Based in New York City with hybrid work model – 3 days on-site minimum in Midtown Manhattan - New York City
- Minimum of 7 years of experience HR People Insights, Analytics, AI enablement
Bachelor’s degree or equivalent experience. A master’s degree is a plus. Equivalent experiences will be considered.
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*Chanel, Inc. reserves the right to edit, change, or make exceptions on designations where circumstances where deemed appropriate.
Compensation:
The anticipated base salary range for this position is $160,000-$190,000. A base salary is one component of the total compensation for this position. Other forms of variable pay [may/will] be offered for this position. Other components [may/will] include bonus potential, benefits, and/or perks.
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Benefits and Perks:
- Wellbeing resources include dedicated paid time off for wellbeing (2-week August Office Closure) and a Wellbeing fund
- Family and care giving benefits (inclusive of parental leave, fertility support, MilkStork, and Care.com Membership)
- Generous paid time off policies to include vacation, holiday, sick and volunteer days
- 401K and other incentives
- Robust healthcare offerings; medical, dental, vision, MDLIVE (virtual care), One Medical, Flexible Spending Accounts (Health Care & Dependent Care), Health Savings Account and Employee Assistance Program
Life insurance, Accidental Death & Dismemberment, Short Term Disability, Long Term Disability, Health Advocate, International Business Travel Accident & Medical, and Commuter Transit & Parking
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Additional Information:
Chanel is a private company whose values are grounded in creating conditions for people to perform at their best and feel fulfilled and confident in their work. We offer a unique work environment where individuals are encouraged to better understand the brand, the business, and motivations, so that together we can unlock the possibilities of growth. This is reflected in:
Diversity and Inclusion:
- At CHANEL, we are intentional in promoting Diversity & Inclusion. We foster respect, empathy, and dignity for all. We believe strongly that the diversity of our people across the full spectrum of human differences is essential to our organisation and the connections we have with each other and our clients.
We offer Employee Resource Groups in the US that are voluntary, open to all, employee-led groups formed around a shared identity or lived experience, whose aim is to foster a diverse, inclusive, and equitable community aligned with the values and missions of the communities they support.
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Chanel Community:
- CHANEL Community empowers our employees to channel their passions, talents and sense of purpose to contribute to and learn from our communities.
Employees are encouraged to take time off annually to volunteer through the CHANEL Community. CHANEL also matches employee donations to select charitable organizations.
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Sustainability:
- CHANEL Mission 1.5° is our climate action plan. It is focused on transforming the business in line with the ambitions of the Paris Agreement on climate change to limit the average global mean temperature increase to 1.5 degrees Celsius above preindustrial levels.
Employees are encouraged to contribute to our US Sustainability efforts at the corporate level and within the divisions, through organized taskforces and initiatives.
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Arts and Culture:
- We are committed to extending our legacy of cultural engagement. Global support includes the CHANEL Culture Fund, which supports a select group of leading art culture institutions across the globe, and the CHANEL Next Prize for the next generation of creative talent. US support currently includes Annual sponsorship of the MoMA film program, Tribeca Film Festival programs and Through Her Lens, Support of the Academy Gold Fellowship for Women and Sponsorship of the BAAND Together Dance Festival at Lincoln Center.
Fondation Chanel :
- Since 2011, Fondation CHANEL’s mission is for women and girls to be free to shape their own destiny. Through multi-year partnerships with financial and technical support, Fondation CHANEL is committed to improving the safety and autonomy of women and adolescent girls around the world, impacting over a million women and girls in its first 10 years.
For more information, please navigate to the Fondation Chanel website here
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Career and Leadership Development:
- We have dedicated in-house teams focused on supporting the onboarding of employees,developing leadership skills via custom programs like Imagine Chanel People, Heart of Leadership and group and individual coaching, and blended online and live classes offered on our Bloom platform and by skilled trainers, such as Shape Your Career, to develop career building skills.
*Chanel, Inc. benefits and perks are dependent on eligibility and subject to modification by Chanel at any time.
Salary Context
This $160K-$190K range is above the median for AI/ML Engineer roles in our dataset (median: $175K across 1356 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 8,943 AI roles we're tracking, AI/ML Engineer positions make up 75% of the market. At CHANEL, 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 $212,000 based on 11,866 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $228,700. This role's midpoint ($175K) sits 17% below the category median. Disclosed range: $160K to $190K.
Across all AI roles, the market median is $213,380. Top-quartile compensation starts at $264,148. The 90th percentile reaches $319,310. For comparison, the highest-paying categories include AI Safety ($253,100) and Research Engineer ($252,000). By seniority level: Entry: $110,408; Mid: $193,200; Senior: $228,700; Director: $272,250; VP: $235,000.
CHANEL AI Hiring
CHANEL has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in New York, NY, US. Compensation range: $190K - $190K.
Location Context
AI roles in New York pay a median of $221,000 across 2,878 tracked positions. That's 4% 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 8,943 open positions tracked in our dataset. By seniority: 175 entry-level, 4,132 mid-level, 3,268 senior, and 1,368 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (521 positions). The remaining 8,351 roles require on-site or hybrid attendance.
The market median for AI roles is $213,380. Top-quartile compensation starts at $264,148. The 90th percentile reaches $319,310. Highest-paying categories: AI Safety ($253,100 median, 57 roles); Research Engineer ($252,000 median, 419 roles); AI Engineering Manager ($251,622 median, 51 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 8,943 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (6,739), AI Product Manager (403), AI Software Engineer (402). 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 (175) are outnumbered by mid-level (4,132) and senior (3,268) 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 1,368 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (521 positions), with 8,351 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 $213,380. Top-quartile roles start at $264,148, and the 90th percentile reaches $319,310. 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 Safety roles lead at $253,100 median, while Prompt Engineer roles sit at $141,440. 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: Python (1,422 postings), Aws (808 postings), Azure (638 postings), Rag (555 postings), Gcp (457 postings), Pytorch (433 postings), Claude (341 postings), Kubernetes (337 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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