Job description

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 business problems 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 risk analysis.  Innovate Predictive & Optimization Solutions for Growth • Develop and deploy predictive 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 incorporate checks to meet regulatory requirements. • Work with functional teams to validate that AI-driven processes maintain integrity and auditability. People Leadership – Cultivate Teams that Innovate • Stay abreast of the latest developments in data science, AI, and relevant industry trends. • Proactively introduce cutting-edge techniques (such as time-series forecasting methods, reinforcement learning for supply chain optimization, or NLP for financial document analysis) as appropriate. • Foster a culture of continuous improvement, where analytical methods are regularly refined and validated against business outcomes. • Mentor junior data scientists and analysts, and promote best practices in coding, experimentation, and knowledge sharing within the analytics community. YOU MUST HAVE • Advanced degree (Bachelor’s or above) in Data Science, Statistics, Computer Science, Operations Research, or related field. • 8+ years of experience in data science or advanced analytics roles, including deploying solutions that drive measurable value (ideally in supply chain and/or finance contexts). • Expert-level programming in Python and SQL; proficiency with libraries/frameworks such as pandas, scikit-learn, TensorFlow/PyTorch; experience with Databricks or Azure Cloud ML services. • Strong grasp of statistical modeling, machine learning algorithms, and data mining techniques for time-series forecasting and classification/regression. • Solid understanding of supply chain (demand forecasting, S&OP, inventory optimization) and finance (budgeting/planning, reporting, cost analysis) concepts. • Excellent problem-solving and ability to break ambiguous problems into actionable data questions; strong communication skills to influence business leaders. WE VALUE • Experience leading data science projects and/or teams; strong collaboration skills across interdisciplinary stakeholders; comfort presenting to executive audiences. • Familiarity with enterprise data environments and tools (e.g., SAP/ERP, supply chain management systems, financial databases) and integrating solutions into production workflows (APIs, dashboards, business applications). • Passion for innovation (competitions, publications, patents) and ability to evaluate and introduce new tools/technologies when they add value. • Results-driven mindset with clear objectives (e.g., reducing forecast error by X% or accelerating financial close by Y days) and tracking against outcomes. • Commitment to continuous learning, including emerging AI trends (Generative AI and agentic AI) and responsible application in business processes. COMPENSATION The annual base salary range for this position is $169,316-$211,645. Please note that this salary information serves as a general guideline. Solstice considers various factors when extending an offer, including but not limited to the scope and responsibilities of the position, the candidate's work experience, education and training, key skills, as well as market and business considerations. BENEFITS OF WORKING FOR SOLSTICE ADVANCED MATERIALS In addition to a competitive salary, leading-edge work, and developing solutions side-by-side with dedicated experts in their fields, Solstice Advanced Materials employees are eligible for a comprehensive benefits package. This package includes employer-subsidized Medical, Dental, Vision, and Life Insurance; Short-Term and Long-Term Disability; 401(k) match, Flexible Spending Accounts, Health Savings Accounts, EAP, and Educational Assistance; Parental Leave, Paid Time Off (for vacation, personal business, sick time, and parental leave), and 12 Paid Holidays. Solstice Advanced Materials is an equal opportunity employer. Qualified applicants will be considered without regard to age, race, creed, color, national origin, ancestry, marital status, affectional or sexual orientation, gender identity or expression, disability, nationality, sex, religion, or veteran status.  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.

Requirements

Must-haves

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 risk analysis.
Innovate Predictive & Optimization Solutions for Growth
Develop and deploy predictive models and optimization algorithms that address critical ISC and other domain problems.
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.
Governance, Compliance, & Safety
Ensure that analytics initiatives adhere to necessary compliance and governance standards. When developing models, ensure they incorporate checks to meet regulatory requirements.
Work with functional teams to validate that AI-driven processes maintain integrity and auditability.
People Leadership – Cultivate Teams that Innovate
Stay abreast of the latest developments in data science, AI, and relevant industry trends.
Proactively introduce cutting-edge techniques (such as time-series forecasting methods, reinforcement learning for supply chain optimization, or NLP for financial document analysis) as appropriate.
Foster a culture of continuous improvement, where analytical methods are regularly refined and validated against business outcomes.
Mentor junior data scientists and analysts, and promote best practices in coding, experimentation, and knowledge sharing within the analytics community.

Nice-to-haves

None flagged.

Application prep

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Keywords to mirror

machine learningaipythonsqlazureml

Platform: oracle-cloud
Effort: medium

Benefits

Benefits detected in the listing.

Dental

Vision

401(K)

Paid Time Off

Parental Leave