Data Scientist II utilizing cutting - edge machine learning and AI solutions at Early Warning Services. Collaborating with cross - functional teams to deliver business results and enhance financial services.
About the role
- Principal Data Scientist providing technical expertise and innovative solutions for Solstice’s analytics initiatives. Leading data-driven projects in supply chain and finance domains.
Responsibilities
- 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.
- 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).
- Identify high-impact analytics opportunities in areas like demand planning, inventory management, financial forecasting, and risk analysis.
- Develop and deploy predictive models and optimization algorithms that address critical ISC and other domain problems.
- Build 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).
- 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.
- 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.
- Ensure that analytics initiatives adhere to necessary compliance and governance standards.
- When developing models, ensure they incorporate checks to meet regulatory requirements.
- Stay abreast of the latest developments in data science, AI, and relevant industry trends.
Requirements
- 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), finance (budgeting/planning, reporting, cost analysis) and similar enterprise function concepts.
- Excellent problem-solving and ability to break ambiguous problems into actionable data questions; strong communication skills to influence business leaders.
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 (for vacation, personal business, sick time, and parental leave)
- 12 Paid Holidays
Job title
Job type
Experience level
Salary
Degree requirement
Tech skills
Location requirements
Data Scientist delivering data science projects for media companies at Samba TV in Warsaw. Collaborating with engineering and mentoring junior data scientists on the team.
Data Scientist role at UTEC focused on analyzing data and building predictive models. Collaborate on various projects and ensure data quality and consistency.
Senior Manager in Data Science & Analytics leading analytics strategies at Circle K. Collaborating with teams to enhance customer experience and loyalty programs.
Vice President leading Claims Data Science at The Hartford. Transforming the Claims customer journey with AI capabilities and overseeing data science initiatives.
Senior Software Engineer for Data Science at GM. Leading AI - driven analytics and prognostics applications for vehicle engineering and customer satisfaction.
Lead Engineer for AV Safety Analytics supporting GM’s autonomous vehicle initiatives. Overseeing large - scale data analyses and safety assurance infrastructure development.
Lead Weather - to - Power Data Scientist improving short - term trading performance at Ørsted. Develop and maintain forecasting models in collaboration with traders, quants, and IT.
Specialized Analytics Lead Analyst role at Citi focused on leveraging machine learning for fraud prevention, conducting data engineering, building predictive models, and managing fraud risks.
Senior Data Scientist at Boeing creating analytic solutions for HR challenges across various locations. Collaborating with HR and data engineering teams to optimize workforce decision - making.