Manager - Operations Research Scientist

About the Business

Adani Group is a leading diversified Indian conglomerate comprising 10 publicly traded companies. It commands a robust presence in logistics and utility infrastructure with nationwide operations and headquarters in Ahmedabad, Gujarat. The group is recognized for large-scale infrastructure development and globally benchmarked operations and maintenance practices. Among its companies, Adani holds the distinction of being India’s only infrastructure investment grade issuer with four IG-rated businesses.

Job Purpose

The Manager - Operations Research Scientist will spearhead the design, development, and deployment of optimization and simulation models to guide data-driven decision-making throughout critical business functions. Leveraging advanced mathematical, statistical, and AI methodologies, this role will optimize processes in ports, logistics, transportation, supply chain, demand planning, manufacturing, and sourcing to enhance operational efficiency, reduce costs, and enable strategic and tactical decisions across the group’s companies.

Key Responsibilities

• Create and implement optimization models focused on logistics, supply chain, manufacturing, and other operational processes to enhance efficiency and cost-effectiveness.
• Apply mathematical optimization techniques, including linear programming, integer programming, combinatorial optimization, and network flow algorithms to support improved business decisions.
• Utilize advanced AI and machine learning methods, hybrid optimization, and simulation modeling to ensure models are scalable and adaptable.
• Integrate optimization approaches into both long-term strategic planning and short-term tactical operations.
• Develop and refine algorithms such as simulated annealing, genetic algorithms, tabu search, Markov decision processes, and ant colony optimization to boost model accuracy and effectiveness.
• Drive automation and optimization through data-driven decision support systems to enhance business workflows.
• Design optimization models for electric vehicle fleet charging strategies, promoting cost-efficient and effective charging operations.
• Use combinatorial optimization, network flow models, and machine learning-based route planning to minimize logistics costs.
• Manage computational complexity by applying decomposition algorithms and building large-scale mathematical models.
• Enable predictive and prescriptive analytics by analyzing historical and real-time data to create optimized operational strategies.
• Apply discrete event simulation to reduce operational disruptions and maximize resource utilization.
• Integrate optimization with forecasting and financial planning for cost savings and risk mitigation.
• Collaborate with business leaders, strategy teams, and data scientists to ensure models align with organizational objectives.
• Partner with IT and engineering units to deploy AI-powered models on scalable cloud infrastructure.
• Translate complex mathematical outcomes into executive-level insights and actionable recommendations.
• Develop governance frameworks to ensure compliance and ethical use of AI-driven optimization solutions.
• Conduct ongoing validation, risk assessments, and fine-tuning to preserve model accuracy and reliability.
• Stay abreast of cutting-edge AI developments, algorithmic innovations, and best practices to continuously advance operations research capabilities.

Collaboration and Stakeholders

• Works internally with business strategy, operations, data science, AI teams, IT, cloud engineering, finance, and risk management departments.
• Engages externally with technology vendors, AI solution providers, academic research bodies, and regulatory authorities to foster innovation and compliance.

Qualifications

• Ph.D. or Master’s degree in Operations Research, Industrial Engineering, Statistics, Applied Mathematics, Computer Science, or relevant disciplines.
• Professional certifications such as Certified Optimization & OR Specialist (e.g., CPLEX, Gurobi), Advanced AI & ML certifications (Google, AWS, Microsoft AI), and Data Science or Statistical Analysis credentials from reputable platforms.
• Possesses 5 to 10 years of practical experience in developing and deploying operations research models within engineering, logistics, manufacturing, or supply chain contexts.