Degree in Data Science, Statistics, Operations Research, Engineering, or related field with at least 3 years of experience
Strong communication skills with the ability to present insights to technical and business audiences
Experience in supply chain analytics, scenario modeling, or decision support roles
Strong proficiency in Python (Pandas, NumPy, scikit-learn) and SQL
Requirements:
Translate planning questions into scenario models that quantify operational, financial, and service trade-offs
Develop what-if analyses to evaluate demand variability, supply constraints, capacity, inventory risk, and financial impacts
Build predictive and prescriptive models (forecasting, optimization, simulation) and conduct sensitivity and risk analyses; partner with data engineering for scalable, production-ready solutions
Develop AI-enabled tools to support scenario analysis workflows, deploy AI Agents to automate planning analyses, and create interactive analytics applications to democratize insights
Job description
Title: Data Scientist
Location: Remote
Duration: 1 year + extensions
Rate: $45/hr
Role Overview
We are seeking a business-facing Data Scientist to support Executive Integrated Business Planning (IBP) and Supply Chain decision-making through advanced scenario modeling, analytics, and AI-enabled solutions.
This role partners closely with business stakeholders to translate planning questions into quantitative analyses, develop scenario-based insights, and implement AI-driven tools that enhance decision velocity and transparency. The position combines business acumen, statistical modeling, and emerging AI/Agentic AI capabilities to modernize digital supply chain workflows.
Key Responsibilities
Scenario Support
Support structured problem framing with Supply Chain and IBP stakeholders.
Translate business questions into scenario models that quantify operational, financial, and service trade-offs.
Develop “what-if” analyses to evaluate demand variability, supply constraints, capacity, inventory risk, and financial impacts.
Prepare executive-ready materials summarizing scenario assumptions, sensitivities, and implications.
Advanced Analytics & Modeling
Build predictive and prescriptive models (forecasting, optimization, simulation) to enhance supply chain planning decisions.
Conduct sensitivity and risk analyses to improve transparency in IBP discussions.
Partner with data engineering teams to ensure scalable and production-ready solutions.
AI & Agentic AI Enablement
Develop AI-enabled tools to support scenario analysis workflows, including automated scenario generation, exception detection, and executive insight summaries.
Build and deploy AI Agents to automate repetitive planning analyses and orchestrate multi-step scenario workflows.
Apply responsible AI practices including validation, monitoring, and governance.
Digital Solution Development
Develop interactive analytics applications (e.g., Streamlit, Dash) to democratize scenario insights.
Support adoption of AI- and data-driven planning capabilities across stakeholders.
Required Qualifications:
Degree in Data Science, Statistics, Operations Research, Engineering, or related field with at least 3 years of experience.
Strong communication skills with the ability to present insights to technical and business audiences.
Experience in supply chain analytics, scenario modeling, or decision support roles.
Familiarity with IBP, S&OP, and supply chain planning processes.
Strong proficiency in Python (Pandas, NumPy, scikit-learn) and SQL.
Experience building predictive, optimization, or simulation models.
Experience developing AI/LLM-enabled solutions or workflow automation tools.
Preferred Qualifications:
Experience developing AI Agents or LLM-orchestrated workflows.
Experience with Databricks, Spark, or cloud platforms (AWS, Azure, GCP).
Knowledge of supply chain financial trade-offs (working capital, service, revenue risk).
Experience in biotech, pharmaceutical, or regulated environments.
Basic Qualification:
Masters degree OR Bachelors degree and 2 years of experience OR Associates degree and 6 years of experience OR High school diploma / GED and 8 years of experience
