Work Location: Hybrid

Job Function R&D;

Grade 30

Manager SHRIDHAR RAIKAR (152873683)

Recruiter Abhilash Toofran (202024425)[C]

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 robust 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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📌 Manager - Advance Analytics (Bengaluru)
🏢 Kenvue
📍 Bengaluru