Data Scientist (Predictive AI - Operational Research)

As a highly motivated and experienced Data Scientist with expertise in Predictive AI and Operational Research (OR), your role will involve driving data-driven decision-making and optimization for complex business processes. You will be responsible for designing, developing, and deploying machine learning and mathematical models to solve real-world operational problems in domains such as supply chain, logistics, manufacturing, finance, and customer service. Key Responsibilities: - Participate in various Predictive AI projects such as Demand Sensing and Forecasting, Price and Promotion Optimization, and others - Utilize Python for implementation - Apply linear optimization algorithms including Linear Programming and Mixed Integer Programming - Implement non-linear optimization algorithms like Gradient-based and Metaheuristic algorithms (e.g., Genetic Algorithm, Simulation Annealing, etc.) - Utilize Simulation techniques such as Montecarlo, MCMC, discreet event, agent-based modeling, etc. - Identify optimization problem types like Max Flow, Schedule Problem, Knapsack problem, etc. - Work with cloud platforms like GCP and AWS - Experience with both commercial and non-commercial solvers including Gurobi, Hexaly, HiGHS, CP-SAT OrTools, etc. Qualifications Required: - Experience in supply chain and pricing/promotion domains is a plus - Deployment experience of models - Proficiency in time series predictive models and feature engineering for time series data - Familiarity with classical ML techniques and CI/CD - Knowledge of Google Cloud (GCP) and Vertex AI Additional Company Details: - Competitive salary & performance-based bonuses - Work from home flexibility / Hybrid options - Continuous learning budget & GenAI certifications - Opportunity to work on cutting-edge AI projects - Dynamic and collaborative team environment Skills: Predictive Modeling, Demand Forecasting, Operations Research, Linear Programming, Python Experience: 3.00-8.00 Years As a highly motivated and experienced Data Scientist with expertise in Predictive AI and Operational Research (OR), your role will involve driving data-driven decision-making and optimization for complex business processes. You will be responsible for designing, developing, and deploying machine learning and mathematical models to solve real-world operational problems in domains such as supply chain, logistics, manufacturing, finance, and customer service. Key Responsibilities: - Participate in various Predictive AI projects such as Demand Sensing and Forecasting, Price and Promotion Optimization, and others - Utilize Python for implementation - Apply linear optimization algorithms including Linear Programming and Mixed Integer Programming - Implement non-linear optimization algorithms like Gradient-based and Metaheuristic algorithms (e.g., Genetic Algorithm, Simulation Annealing, etc.) - Utilize Simulation techniques such as Montecarlo, MCMC, discreet event, agent-based modeling, etc. - Identify optimization problem types like Max Flow, Schedule Problem, Knapsack problem, etc. - Work with cloud platforms like GCP and AWS - Experience with both commercial and non-commercial solvers including Gurobi, Hexaly, HiGHS, CP-SAT OrTools, etc. Qualifications Required: - Experience in supply chain and pricing/promotion domains is a plus - Deployment experience of models - Proficiency in time series predictive models and feature engineering for time series data - Familiarity with classical ML techniques and CI/CD - Knowledge of Google Cloud (GCP) and Vertex AI Additional Company Details: - Competitive salary & performance-based bonuses - Work from home flexibility / Hybrid options - Continuous learning budget & GenAI certifications - Opportunity to work on cutting-edge AI projects - Dynamic and collaborative team environment Skills: Predictive Modeling, Demand Forecasting, Operations Research, Linear Programming, Python Experience: 3.00-8.00 Years