Forsyth Barnes
Senior Data Scientist, Supply Chain Optimization
Forsyth Barnes, Weehawken, New Jersey, United States
Title:
Senior Data Scientist, Supply Chain Optimization (Ref: 191387) Salary:
$230,000-275,000 + Bonus & LTI Locations:
NYC, San Fran, or Dallas Our client is a leading organization in the retail industry, particularly in the apparel and accessories sector. They are dedicated to leveraging advanced analytics and innovative strategies to enhance operational effectiveness and drive superior business outcomes. With a strong commitment to sustainable practices and a customer-centric focus, they aim to lead the market while making a positive contribution to societal welfare. This is an exciting opportunity for a Senior Data Scientist to play a crucial role in optimizing the supply chain. The ideal candidate will bring extensive data science expertise to tackle complex challenges and align with the strategic goals of the organization. Requirements Demonstrated experience in developing predictive or optimization models related to supply chain, value chain, or manufacturing operations. Expertise in Python, R, Spark, Hive, and SQL for large-scale data manipulation in both on-premises and cloud environments (e.g., Azure, AWS, GCP). In-depth knowledge of machine learning and statistical modeling techniques, including regression, time-series forecasting, boosted trees, neural networks, and reinforcement learning. Familiar with optimization and simulation methods such as mixed-integer programming, heuristics, and Monte Carlo simulation. Proven capability in translating analytical insights into actionable operational strategies with quantifiable business impact. Strong collaboration and communication abilities; capable of effectively engaging with engineering, operations, and executive teams. Experience in leading data-driven projects that have transformed supply or value chains. Key Responsibilities Develop, validate, and maintain ML/AI models to drive improvements throughout the value chain, including demand forecasting, inventory optimization, dynamic replenishment, and transportation efficiency. Create algorithms and automated processes that integrate, clean, and assess large datasets from various operational systems such as procurement, manufacturing, logistics, and sales. Design and implement optimization frameworks to simulate supply scenarios, assess trade-offs (cost, speed, sustainability), and recommend data-driven solutions. Work collaboratively with cross-functional teams in operations, planning, sourcing, and technology to develop scalable data pipelines and modeling workflows. Effectively communicate actionable insights derived from complex datasets to business stakeholders to inform strategic planning and execution. Provide technical leadership on model architecture, data science best practices, and AI governance. Define strategy and set priorities for the data science team supporting value chain analytics, including planning and resource allocation.
Senior Data Scientist, Supply Chain Optimization (Ref: 191387) Salary:
$230,000-275,000 + Bonus & LTI Locations:
NYC, San Fran, or Dallas Our client is a leading organization in the retail industry, particularly in the apparel and accessories sector. They are dedicated to leveraging advanced analytics and innovative strategies to enhance operational effectiveness and drive superior business outcomes. With a strong commitment to sustainable practices and a customer-centric focus, they aim to lead the market while making a positive contribution to societal welfare. This is an exciting opportunity for a Senior Data Scientist to play a crucial role in optimizing the supply chain. The ideal candidate will bring extensive data science expertise to tackle complex challenges and align with the strategic goals of the organization. Requirements Demonstrated experience in developing predictive or optimization models related to supply chain, value chain, or manufacturing operations. Expertise in Python, R, Spark, Hive, and SQL for large-scale data manipulation in both on-premises and cloud environments (e.g., Azure, AWS, GCP). In-depth knowledge of machine learning and statistical modeling techniques, including regression, time-series forecasting, boosted trees, neural networks, and reinforcement learning. Familiar with optimization and simulation methods such as mixed-integer programming, heuristics, and Monte Carlo simulation. Proven capability in translating analytical insights into actionable operational strategies with quantifiable business impact. Strong collaboration and communication abilities; capable of effectively engaging with engineering, operations, and executive teams. Experience in leading data-driven projects that have transformed supply or value chains. Key Responsibilities Develop, validate, and maintain ML/AI models to drive improvements throughout the value chain, including demand forecasting, inventory optimization, dynamic replenishment, and transportation efficiency. Create algorithms and automated processes that integrate, clean, and assess large datasets from various operational systems such as procurement, manufacturing, logistics, and sales. Design and implement optimization frameworks to simulate supply scenarios, assess trade-offs (cost, speed, sustainability), and recommend data-driven solutions. Work collaboratively with cross-functional teams in operations, planning, sourcing, and technology to develop scalable data pipelines and modeling workflows. Effectively communicate actionable insights derived from complex datasets to business stakeholders to inform strategic planning and execution. Provide technical leadership on model architecture, data science best practices, and AI governance. Define strategy and set priorities for the data science team supporting value chain analytics, including planning and resource allocation.