Manager - Advance Analytics

Kenvue Is Currently Recruiting For a

Manager - Advance Analytics

What We Do

At Kenvue, we realize the extraordinary power of everyday care. Built on over a century of heritage and rooted in science, we’re the house of iconic brands - including NEUTROGENA®, AVEENO®, TYLENOL®, LISTERINE®, JOHNSON’S® and BAND-AID® that you already know and love. Science is our passion; care is our talent.

Who We Are

Our global team is ~ 22,000 brilliant people with a workplace culture where every voice matters, and every contribution is appreciated. We are passionate about insights, innovation and committed to delivering the best products to our customers. With expertise and empathy, being a Kenvuer means having the power to impact millions of people every day. We put people first, care fiercely, earn trust with science and solve with courage – and have brilliant opportunities waiting for you! Join us in shaping our future–and yours. For more information, click here.

Role Reports To

Senior Manager - Forecasting & Analytics

Location:

Asia Pacific, India, Karnataka, Bangalore

Work Location:

Hybrid

Role Summary

What you will do

The Manager – Advanced Analytics will lead the design, development, and scaling of advanced analytics solutions that drive enterprise decision-making across forecasting, machine learning, and agentic AI use cases within the broader analytics and decision intelligence ecosystem.

This role requires strong hands-on experience in advanced forecasting, machine learning, and modern AI approaches including agentic AI. The manager will be accountable for translating business problems into scalable analytical products, taking solutions from problem framing and model design → MVP → production deployment, while driving measurable business impact through predictive, prescriptive, and intelligent automation capabilities.

Key Responsibilities

Advanced Forecasting, ML & Agentic AI

• Lead the design and deployment of advanced forecasting solutions across demand, supply, commercial, or operational use cases using statistical, machine learning, and hybrid modeling approaches.
• Build and productionize machine learning models for prediction, classification, segmentation, anomaly detection, and decision support.
• Drive the adoption of agentic AI capabilities to automate insight generation, exception triaging, scenario evaluation, and decision workflows.
• Define fit-for-purpose approaches that combine forecasting, ML, optimization, and GenAI/agentic patterns based on business value, scalability, and explainability.
• Apply human-in-the-loop, governance, and monitoring practices to ensure reliability, auditability, and responsible AI usage.
  
  

• Develop and review advanced forecasting, predictive, and causal models using time-series methods, machine learning, and deep learning techniques.
• Establish robust practices for feature engineering, model evaluation, backtesting, accuracy measurement, and model monitoring.
• Translate complex analytical outputs into business recommendations and executive-ready narratives that support decision-making.
  
  

• Deploy and operationalize forecasting, ML, and agentic AI solutions on enterprise cloud platforms such as Azure, including model training, versioning, deployment, and monitoring.
• Integrate analytical solutions with enterprise data platforms, business applications, and decision workflows.
• Define reusable modeling, deployment, and orchestration standards to improve scalability and speed to value.
• Ensure solutions meet enterprise expectations for security, reliability, scalability, and Responsible AI compliance
  
  

• Own delivery of advanced analytics initiatives from use-case identification and experimentation → MVP → production.
• Partner with Product, IT, Data Engineering, and Business leaders to identify high-impact opportunities and drive adoption.
• Translate analytical and AI outputs into clear business actions, value stories, and executive-ready recommendations.
  
  

• Lead, mentor, and grow a team of analysts, data scientists, and ML practitioners.
• Build deep capability in advanced forecasting, machine learning, experimentation, and agentic AI.
• Drive technical design reviews, best practices, and cross-team knowledge sharing.
  
  

• Bachelor’s or Master’s degree in Statistics, Mathematics, Computer Science, Engineering, Economics, Operations Research, or a related quantitative field.
• 8–10 years of experience in advanced analytics, data science, forecasting, or machine learning, with a strong record of production deployment.
• Hands-on experience in advanced forecasting techniques, including statistical, machine learning, and hybrid forecasting methods.
• Strong expertise in machine learning, model evaluation, experimentation, and analytical problem solving.
• Exposure to or hands-on experience with agentic AI / GenAI-enabled analytical workflows, such as intelligent automation, insight generation, or decision support agents.
• Proficiency in Python and SQL, with experience building production-grade analytics solutions.
• Experience deploying analytics or AI solutions on Azure or comparable cloud platforms.
• Proven experience leading teams and influencing cross-functional and senior stakeholders.
  
  

• Experience with demand forecasting, supply chain analytics, commercial analytics, or decision intelligence platforms.
• Exposure to optimization, causal AI, scenario modeling, or simulation-based decisioning.
• Familiarity with MLOps, Responsible AI, risk controls, and governance for AI/GenAI systems.
• Experience working in consumer goods, supply chain, operations, finance, or commercial analytics domains.
  
  

• Advanced analytics solutions deployed in production with measurable business adoption and value realization.
• Improved forecast accuracy, decision quality, and speed to insight across key business workflows.
• Scalable use of ML and agentic AI capabilities across multiple business use cases.
• Strong uplift in team capability across forecasting, advanced analytics, and intelligent automation.