Manager - Advance Analytics

Manager - Advance Analytics

O que fazemos

At Kenvue, percebemos o extraordinário poder do cuidado diário. Construída com base em mais de um século de herança e enraizada na ciência, somos a casa de marcas icônicas - incluindo NEUTROGENA®, AVEENO®, TYLENOL,® LISTERINE,® JOHNSON'S® e BAND-AID® que você já conhece e ama. A ciência é a nossa paixão; O cuidado é o nosso talento.

Quem somos

Nossa equipe global é de ~ 22.000 pessoas brilhantes com uma cultura no local de trabalho onde cada voz é importante e cada contribuição é apreciada. Somos apaixonados por insights, inovação e comprometidos em entregar os melhores produtos aos nossos clientes. Com experiência e empatia, ser um Kenvuer significa ter o poder de impactar milhões de pessoas todos os dias. Colocamos as pessoas em primeiro lugar, nos importamos ferozmente, ganhamos confiança com a ciência e resolvemos com coragem - e temos oportunidades brilhantes esperando por você! Junte-se a nós para moldar nosso futuro - e o seu. Para obter mais informações, clique em aqui.

Role reporta para:

Senior Manager - Forecasting & Analytics

Localização:

Asia Pacific, India, Karnataka, Bangalore

Local de trabalho:

Híbrido

O que você fará

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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