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About This Role
Supply Chain Operations Senior Manager \| Senior Level \| Full time
Job No. 13687440 \| Multiple Locations
- *This position is required to be ONSITE in New York.*
Accenture is one of the world’s leading providers of Supply Chain services, we help our clients architect, build and operate high performance supply chain organizations through our global and flexible solutions. At Accenture, we partner with forward\-thinking business leaders, of the world’s most dynamic companies, to transform supply chain and drive sustainable changes to their cost structures.
As one of the leading supply chain operations specialist, Accenture excels at helping companies build the foundation for long\-term growth. We are committed to delivering exceptional service through our exceptional people, and as an employee you’d enjoy a fulfilling career in an innovative environment where challenging and interesting work is part of daily life.
Join Accenture and help transform leading organizations and communities around the world. The sheer scale of our capabilities and client engagements and the way we collaborate, operate and deliver value provides an unparalleled opportunity to grow and advance. Choose Accenture, and make delivering innovative work part of your extraordinary career.
Accenture people build careers in four different areas of our business: Consulting, Technology, Business Process Services and internal Corporate Functions. Each area offers a unique career experience and a compelling mix of work and training opportunities, work environment and structure for career progression.
Accenture professionals work on projects across a range of business processes, business applications and information technology. They may provide technology services, such as application management, infrastructure management and systems integration, or they may deliver business process services, including finance and accounting, procurement and human resources. Depending on the role, Business Process Services professionals may be based at a client’s office or in one of Accenture’s 50 delivery centers around the world.
- *This position is required to be ONSITE in New York.*
You Are:
Accenture is seeking a dynamic and results\-oriented Supply Chain Operations Senior Manager. In this role, you will collaborate with external / internal clients to execute supply chain operations such as, SC Planning and Fulfillment, Materials Management, and Product Master Data Maintenance, continuous improvement initiatives and ensure supply chain solutions are addressing related client metrics and contracted SLAs for designated service. Manage delivery of practice services including inventory management and operational cost savings achievement. Demonstrate mastery in forecasting and scheduling, strategic development and performance delivery of the supply chain operations function.
The Work:
Lead Global Demand Planning:
- Architect and manage the global demand planning process, ensuring robust statistical forecasting, demand signal integration, and scenario planning across multiple business units and geographies.
Advanced Forecasting \& Analytics:
- Deploy and optimize advanced forecasting models (e.g., ARIMA, exponential smoothing, machine learning algorithms) using platforms such as O9, Databricks, SAP IBP, and Forecast Pro.
Data Integration \& Automation:
- Integrate demand signals from multiple sources (historical sales, POS, market intelligence, promotions, external data) into a unified planning platform. Automate data pipelines and reporting dashboards using tools like Power BI, Tableau, and SAP Analytics Cloud.
S\&OP Process Leadership:
- Lead the monthly S\&OP cycle, facilitating cross\-functional consensus meetings, scenario modeling, and risk mitigation strategies. Ensure seamless alignment between demand, supply, finance, and commercial teams.
Inventory Optimization:
- Apply advanced inventory optimization techniques (multi\-echelon, safety stock modeling, ABC/XYZ analysis) to balance service levels, working capital, and supply constraints.
Exception Management:
- Develop and implement exception\-based planning workflows, leveraging alerts and root\-cause analytics to proactively address forecast deviations and demand\-supply gaps.
Digital Transformation:
- Drive digital transformation initiatives in demand planning, including the adoption of AI/ML\-based forecasting, digital twins, and real\-time analytics.
Master Data Governance:
- Ensure accuracy and completeness of planning\-relevant master data (product, customer, location) across all systems (SAP ECC, SAP S/4HANA, EDM).
Continuous Improvement:
- Lead Kaizen, Lean, or Six Sigma projects to streamline demand planning processes, reduce forecast error, and enhance planning cycle efficiency.
Team Development:
- Mentor and upskill the demand planning team in advanced analytics, planning systems, and best\-in\-class methodologies.
Here's what you need:
- Minimum 10 years of experience managing global planning operations within the retail, consumer products, or packaging industry (beauty sector experience preferred).
Bonus points if:
- Preferably MBA or relevant post graduate degree in Business, Supply Chain or related field; bachelor’s degree or higher in Business, Supply Chain, Economics, or related field (minimum)
- Deep expertise in statistical forecasting, demand sensing, and causal modeling.
- Experience implementing and leading S\&OP/IBP processes, including scenario planning and what\-if analysis.
- Familiarity with cloud\-based planning platforms and API integrations.
- Experience with automation tools (UiPath, Alteryx) for planning process efficiency.
- Strong knowledge of inventory optimization, replenishment algorithms, and supply chain network modeling.
- Experience in change management and digital transformation within supply chain planning.
- Experience in planning software(O9\) / ERP Ariba SAP \& ECC modules and latest digitization trends in Supply Chain
- Knowledge of beauty industry and regional / affiliate market trends
- Relationship management \- build and maintain relationships with clients, suppliers and colleagues
Compensation at Accenture varies depending on a wide array of factors, which may include but are not limited to the specific office location, role, skill set, and level of experience. As required by local law, Accenture provides a reasonable range of compensation for roles that may be hired as set forth below.
We anticipate this job posting will be posted on 02/03/2026 and open for at least 3 days.
Accenture offers a market competitive suite of benefits including medical, dental, vision, life, and long\-term disability coverage, a 401(k) plan, bonus opportunities, paid holidays, and paid time off. See more information on our benefits here:
U.S. Employee Benefits \| Accenture
Role Location Annual Salary Range
California $132,500 to $245,600
Cleveland $122,700 to $196,500
Colorado $132,500 to $212,200
District of Columbia $141,100 to $226,000
Illinois $122,700 to $212,200
Maryland $132,500 to $212,200
Massachusetts $132,500 to $226,000
Minnesota $132,500 to $212,200
New York $122,700 to $245,600
New Jersey $141,100 to $245,600
Washington $141,100 to $226,000
New York City, NY
Hartford, CT
Morristown, NJ
Philadelphia, PA
Requesting an Accommodation
Accenture is committed to providing equal employment opportunities for persons with disabilities or religious observances, including reasonable accommodation when needed. If you are hired by Accenture and require accommodation to perform the essential functions of your role, you will be asked to participate in our reasonable accommodation process. Accommodations made to facilitate the recruiting process are not a guarantee of future or continued accommodations once hired.
If you would like to be considered for employment opportunities with Accenture and have accommodation needs such as for a disability or religious observance, please call us toll free at 1 (877\) 889\-9009 or send us an email or speak with your recruiter.
Equal Employment Opportunity Statement
We believe that no one should be discriminated against because of their differences. All employment decisions shall be made without regard to age, race, creed, color, religion, sex, national origin, ancestry, disability status, veteran status, sexual orientation, gender identity or expression, genetic information, marital status, citizenship status or any other basis as protected by federal, state, or local law. Our rich diversity makes us more innovative, more competitive, and more creative, which helps us better serve our clients and our communities.
Accenture is an EEO and Affirmative Action Employer of Veterans/Individuals with Disabilities.
Accenture is committed to providing veteran employment opportunities to our service men and women.
Other Employment Statements
Applicants for employment in the US must have work authorization that does not now or in the future require sponsorship of a visa for employment authorization in the United States.
Candidates who are currently employed by a client of Accenture or an affiliated Accenture business may not be eligible for consideration.
Job candidates will not be obligated to disclose sealed or expunged records of conviction or arrest as part of the hiring process. Further, at Accenture a criminal conviction history is not an absolute bar to employment.
The Company will not discharge or in any other manner discriminate against employees or applicants because they have inquired about, discussed, or disclosed their own pay or the pay of another employee or applicant. Additionally, employees who have access to the compensation information of other employees or applicants as a part of their essential job functions cannot disclose the pay of other employees or applicants to individuals who do not otherwise have access to compensation information, unless the disclosure is (a) in response to a formal complaint or charge, (b) in furtherance of an investigation, proceeding, hearing, or action, including an investigation conducted by the employer, or (c) consistent with the Company's legal duty to furnish information.
California requires additional notifications for applicants and employees. If you are a California resident, live in or plan to work from Los Angeles County upon being hired for this position, please for additional important information.
Please read Accenture’s Recruiting and Hiring Statement for more information on how we process your data during the Recruiting and Hiring process.
We work with one shared purpose: to deliver on the promise of technology and human ingenuity. Every day, more than 775,000 of us help our stakeholders continuously reinvent. Together, we drive positive change and deliver value to our clients, partners, shareholders, communities, and each other.
We believe that delivering value requires innovation, and innovation thrives in an inclusive and diverse environment. We actively foster a workplace free from bias, where everyone feels a sense of belonging and is respected and empowered to do their best work.
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Join Accenture to work at the heart of change. Visit us at www.accenture.com.
Salary Context
This $122K-$245K range is above the 75th percentile for AI/ML Engineer roles in our dataset (median: $100K across 15465 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 26,159 AI roles we're tracking, AI/ML Engineer positions make up 91% of the market. At Logic, Inc., 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 $166,983 based on 13,781 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $227,400. This role's midpoint ($184K) sits 10% above the category median. Disclosed range: $122K to $245K.
Across all AI roles, the market median is $184,000. Top-quartile compensation starts at $244,000. The 90th percentile reaches $309,400. For comparison, the highest-paying categories include AI Engineering Manager ($293,500) and AI Architect ($292,900). By seniority level: Entry: $76,880; Mid: $131,300; Senior: $227,400; Director: $244,288; VP: $234,620.
Logic, Inc. AI Hiring
Logic, Inc. has 47 open AI roles right now. They're hiring across AI/ML Engineer, AI Software Engineer, AI Consultant. Positions span New York, NY, US, Atlanta, GA, US, Chicago, IL, US. Compensation range: $93K - $434K.
Location Context
AI roles in New York pay a median of $200,000 across 1,670 tracked positions. That's 9% 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 26,159 open positions tracked in our dataset. By seniority: 2,416 entry-level, 16,247 mid-level, 5,153 senior, and 2,343 leadership roles (Director, VP, C-Level). Remote roles make up 7% of the market (1,863 positions). The remaining 24,200 roles require on-site or hybrid attendance.
The market median for AI roles is $184,000. Top-quartile compensation starts at $244,000. The 90th percentile reaches $309,400. Highest-paying categories: AI Engineering Manager ($293,500 median, 28 roles); AI Architect ($292,900 median, 108 roles); AI Safety ($274,200 median, 19 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 26,159 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (23,752), AI Software Engineer (598), AI Product Manager (594). 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 (2,416) are outnumbered by mid-level (16,247) and senior (5,153) 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 2,343 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 7% of all AI roles (1,863 positions), with 24,200 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 $184,000. Top-quartile roles start at $244,000, and the 90th percentile reaches $309,400. 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 $122,200. 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 (16,749 postings), Aws (8,932 postings), Rust (7,660 postings), Python (3,815 postings), Azure (2,678 postings), Gcp (2,247 postings), Prompt Engineering (1,469 postings), Openai (1,269 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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