Data Scientist

10-12 Years

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Posted a month ago

Job Description

Role Summary

The Principal Data Scientist is the technical and strategic owner of scenario planning across the organization. This role defines the global scenario architecture, ensures alignment with IBP and S&OP, leads multi-domain modeling (demand/supply/network), and drives the adoption of simulation, optimization, and agentic AI-based scenario engines. Acts as a senior advisor to Directors and VPs.

Key Responsibilities

Design and govern the enterprise-wide scenario planning framework, including templates, taxonomies, and scalability standards.
Build multi-layer simulation frameworks (deterministic, stochastic, Monte Carlo, empirical).
Define relationships between scenario outputs and planning decisions (e.g., SL trade-offs, buffer logic, allocation rules, capacity constraints).
Lead cross-functional scenario reviews with Finance, Category, Factory Ops, and Regional Planning.
Identify and formalize structural drivers of risk: forecast drift, bias, lead-time volatility, cannibalization, velocity shifts, market shocks.
Architect the technical foundation for the scenario engine (configs, abstraction layers, ML/optimization modules).
Drive integration into IBP/S&OP cycles, including automated updates and governance.
Mentor Expert and Specialist DSs; define capability roadmap for the scenario DSC (Data Science Center of Excellence).
Represent DS in executive forums; simplify technical concepts for senior leadership.
Ensure compliance with model governance, explainability, auditability, and risk controls.

Required Skills & Experience

10+ years in Data Science, Decision Science, Optimization, or Scenario/Risk modeling.
Deep knowledge of scenario planning, stochastic methods, optimization theory, and forecasting analytics.
Experience designing large-scale decision systems for planning (IBP, S&OP, supply/demand).
Strong Python engineering + architectural design capability.
Familiarity with Gurobi/OR-Tools, PyMC, Monte Carlo simulation engines, and time-series decomposition.
Experience building frameworks, not just models; ability to define system-level abstractions.
Excellent communication and executive influencing capability.

Preferred Experience

Led scenario engines in global supply chains (consumer electronics, FMCG, automotive).
Experience with agentic AI orchestration and LLM-assisted decision systems.

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Job ID: 147075465

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Last Updated: 31-05-2026 06:02:33 PM

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