Manager - Advance Analytics

Manager - Advance Analytics

Ce que nous faisons

Chez Kenvue, nous réalisons le pouvoir extraordinaire des soins quotidiens. S'appuyant sur plus d'un siècle d'héritage et enraciné dans la science, nous sommes la maison de marques emblématiques - dont NEUTROGENA®, AVEENO®, TYLENOL®, LISTERINE®, JOHNSON'S® et BAND-AID® que vous connaissez et aimez déjà. La science est notre passion ; Le soin est notre talent.

Qui nous sommes

Notre équipe mondiale est composée de ~ 22 000 personnes brillantes avec une culture d'entreprise où chaque voix compte et chaque contribution est appréciée. Nous sommes passionnés par les idées, l'innovation et l'engagement à fournir les meilleurs produits à nos clients. Avec de l'expertise et de l'empathie, être un Kenvuer signifie avoir le pouvoir d'avoir un impact sur des millions de personnes chaque jour. Nous donnons la priorité aux personnes, nous nous soucions farouchement, nous gagnons la confiance grâce à la science et nous résolvons les problèmes avec courage - et nous vous offrons de brillantes opportunités ! Joignez-vous à nous pour façonner notre avenir et le vôtre. Pour plus d'informations, cliquez sur ici.

Role relève à :

Senior Manager - Forecasting & Analytics

Lieu :

Asia Pacific, India, Karnataka, Bangalore

Lieu de travail :

Hybride

Ce que tu vas faire

Role Summary

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.

Advanced Analytics & Modelling Foundations

• 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.

Architecture, Platform & Deployment

• 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

Delivery & Stakeholder Leadership

• 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.

People & Capability Leadership

• 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.

Required Qualifications (Must‑Have)

• 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.

Preferred (Still Valuable, Not Mandatory)

• 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.

Success Measures

• 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.

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