Lead Data Scientist

As a Lead Data Scientist at Solstice, you will leverage deep expertise in data science to drive transformative analytics initiatives in our Integrated Supply Chain (ISC), Finance and other similar domains. You will apply advanced machine learning and statistical techniques to solve complex businessproblems in these areas, from demand forecasting and inventory optimization to financial modeling and anomaly detection. You will report directly to our Director of IT, AI, Analytics and Automation, and you'll work out of our Morris Plains, NJ location, on a hybrid work schedule.In this role, you will also serve as a bridge between technical teams and business stakeholders in Supply Chain and Finance, ensuring data-driven insights translate into tangible business value. This position is ideal for a strategic thinker with strong applied data science skills who can combine domain knowledge with technical innovation to improve operational efficiency and financial outcomes. The role exemplifies our Solstice values and behaviors by demonstrating ownership, accountability, collaboration and a continuous improvement mindset, while fostering trust, transparency, and ethical decision making across the organization.At Solstice, our people play a critical role in developing and assisting our employees to help them perform at their best and drive change across the company. Help build a strong, diverse team by recruiting talent, identifying and developing successors, driving retention and engagement, and fostering an inclusive culture.KEY RESPONSIBILITIES:Drive AI Innovation that Delivers Customer-Focused Impact- Lead the design and implementation of Gen AI for tailored AI predictions in the manufacturing and supply chain space.- Spearhead development of Agentic architectures, including multi-agent patterns, deliver innovative AI solutions.- Identify high-impact opportunities in demand planning, inventory management, financial forecasting, and document processing.Continuously Improve Insights Across Key Business Domains- Provide deep data science expertise and thought leadership in Supply Chain and Finance functions, understanding domain-specific challenges and KPIs (e.g., forecast accuracy, working capital, cost variances). I- Identify high-impact analytics opportunities in areas like demand planning, inventory management, financial forecasting, and riskve models and optimization algorithms that address critical ISC and other domain problems.- This includes building machine learning models for forecasting (e.g. supply and demand, cash flow), anomaly detection in financial transactions, optimization of supply chain networks, and other applied AI & Gen AI solutions.- Ensure models are robust, scalable, and deliver measurable improvements (e.g. increased forecast accuracy, reduced costs). Own-It, End-to-End Projects- Lead end-to-end data science projects – defining concrete opportunities from vague problem statements, data extraction and exploration through model training, validation, and deployment.- Work hands-on with large, complex datasets (e.g., ERP data, supply chain data, financial ledgers) to extract insights.- Maintain high standards of data quality and model performance, and implement MLOps best practices for versioning, monitoring, and continuous improvement of models in production.Advance Together Through Strong Cross-Functional Partnerships- Partner closely with Supply Chain analysts, Logistics managers, Finance controllers, and IT data teams to gather requirements and implement data-driven solutions.- Translate complex analytical findings into actionable business insights (e.g. identifying drivers of inventory write-offs or cost overruns) and communicating these insights to non-technical stakeholders to inform decision-making.Governance, Compliance, & Safety- Ensure that analytics initiatives adhere to necessary compliance and governance standards. When developing models, ensure they incorp