Lead Data Scientist

Solstice Advanced Materials; Morris Plains (NJ); Hybrid; USD 169,000 - 212,000; Full time

Benefits offered by this job

Medical Insurance

Dental Insurance

Vision Insurance

401(k) match

Educational Assistance

Parental Leave

Job summary

Solstice Advanced Materials is seeking a Lead Data Scientist based in Morris Plains, NJ, with a hybrid work arrangement. You will own end-to-end data science initiatives, from problem shaping to production-ready models, targeting ISC, Finance, and related domains.

You will lead Gen AI and agentic solution designs, drive impactful analytics, and mentor a team of data scientists. Strong Python/SQL skills and 8+ years' experience are required, with expertise in Databricks or Azure ML and MLOps.

Qualifications

• Advanced degree (Bachelor’s or above) in Data Science, Statistics, Computer Science, Operations Research, or a related field.
• 8+ years of experience in data science or advanced analytics roles, including deployment of solutions that drive measurable value.
• Expert-level programming in Python and SQL, with libraries such as pandas, scikit-learn, TensorFlow, or PyTorch, and 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 concepts (demand forecasting, S&OP, inventory optimization) and finance concepts (budgeting/planning, reporting, cost analysis).
• Excellent problem-solving skills, ability to break ambiguous problems into actionable data questions, and strong communication skills to influence business leaders.

Responsibilities

• Lead the design and implementation of Gen AI approaches for tailored AI predictions in manufacturing and supply chain settings.
• Drive the development of agentic architectures, including multi-agent patterns, to deliver innovative AI solutions.
• Spot and prioritize high-impact analytics opportunities across demand planning, inventory management, financial forecasting, and document processing.
• Apply deep data science expertise and thought leadership to Supply Chain and Finance, focusing on KPIs like forecast accuracy and cost variances.
• Develop and deploy predictive models and optimization algorithms addressing critical ISC and other domain problems.
• Mentor junior data scientists and analysts, and advance best practices in coding, experimentation, and knowledge sharing.

Skills

Python

SQL

Pandas

Scikit-learn

TensorFlow

PyTorch

Education

Advanced degree in data science / stats / CS

Tools

Databricks

Azure Cloud ML

MLOps

Job description

Solstice Advanced Materials is seeking a Lead Data Scientist to drive transformative analytics and Generative AI and agentic solutions across Integrated Supply Chain (ISC), Finance, and related business domains. This hybrid role is based in Morris Plains, NJ, with end-to-end ownership of data science initiatives, from shaping ambiguous problem statements to delivering production-ready models and measurable outcomes.

What you’ll do

• Lead the design and implementation of Gen AI approaches for tailored AI predictions in manufacturing and supply chain settings.
• Drive the development of agentic architectures, including multi-agent patterns, to deliver innovative AI solutions.
• Spot and prioritize high-impact analytics opportunities across demand planning, inventory management, financial forecasting, and document processing.
• Apply deep data science expertise and thought leadership to Supply Chain and Finance, with focus on domain challenges and KPIs such as forecast accuracy, working capital, and cost variances.
• Develop and deploy predictive models and optimization algorithms addressing critical ISC and other domain problems.
• Build forecasting and applied AI solutions for supply and demand, cash flow forecasting, financial anomaly detection, and supply chain network optimization.
• Ensure models are robust and scalable, producing measurable improvements such as increased forecast accuracy and reduced costs.
• Own end-to-end data science projects: define concrete opportunities from vague problem statements, perform data extraction and exploration, and manage model training, validation, and deployment.
• Work hands-on with large, complex datasets such as ERP data, supply chain data, and financial ledgers to generate actionable insights.
• Maintain high data quality and model performance, applying MLOps best practices for versioning, monitoring, and continuous improvement in production.
• Partner 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 for non-technical stakeholders, such as identifying drivers of inventory write-offs or cost overruns.
• Support compliance and governance standards, including checks built into models to meet regulatory requirements.
• Work with functional teams to validate that AI-driven processes preserve integrity and auditability.
• Stay current with developments in data science and AI, and introduce techniques as appropriate, including time-series forecasting methods, reinforcement learning for supply chain optimization, and NLP for financial document analysis.
• Promote continuous improvement by refining and validating analytical methods against business outcomes.
• Mentor junior data scientists and analysts, and advance best practices in coding, experimentation, and knowledge sharing.

Required qualifications

• Advanced degree (Bachelor’s or above) in Data Science, Statistics, Computer Science, Operations Research, or a related field.
• 8+ years of experience in data science or advanced analytics roles, including deployment of solutions that drive measurable value, ideally in supply chain and/or finance contexts.
• Expert-level programming in Python and SQL, with proficiency in libraries such as pandas, scikit-learn, TensorFlow, or PyTorch, and 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 concepts (demand forecasting, S&OP, inventory optimization) and finance concepts (budgeting/planning, reporting, cost analysis).
• Excellent problem-solving skills, ability to break ambiguous problems into actionable data questions, and strong communication skills to influence business leaders.

Technologies you’ll work with

• Python, SQL, pandas, scikit-learn, TensorFlow, PyTorch
• Databricks, Azure Cloud ML services
• MLOps
• ERP (including SAP/ERP), APIs, dashboards

Benefits

• Employer-subsidized Medical, Dental, Vision, and Life Insurance
• Short-Term and Long-Term Disability
• 401(k) match
• Flexible Spending Accounts
• Health Savings Accounts
• EAP
• Educational Assistance
• Parental Leave
• Paid Time Off (vacation, personal business, sick time, and parental leave)
• 12 Paid Holidays

Compensation

The annual base salary range for this position is $169,316 - $211,645.

Role fit (what you bring)

• Experience leading data science projects and/or teams, with strong collaboration across interdisciplinary stakeholders and comfort presenting to executive audiences.
• Familiarity with enterprise data environments and tools (such as SAP/ERP, supply chain management systems, and financial databases), including integrating solutions into production workflows using APIs, dashboards, and business applications.
• Passion for innovation through competitions, publications, or patents, and the ability to evaluate and introduce new tools and technologies when they add value.
• A results-driven mindset with clear objectives tracked against outcomes (for example, reducing forecast error or accelerating financial close).
• Commitment to continuous learning, including responsible use of Generative AI and agentic AI in business processes.