Data & Analytics (D&A) Developer II

Summary:

• Location: Greenville, SC or Atlanta, GA
• Work Mode: Hybrid
• Duration: 12 Months

Responsibilities:

• Act as the bridge between Engineering domain data knowledge, business planning, operations, and IT execution team.
• Build scenario planning models to test critical business assumptions and track project execution.
• Support centralized business operations and program reporting to deliver harmonized insights to stakeholders worldwide.
• Develop and validate Machine Learning models for demand forecasting and predictive use cases.
• Design and execute scenario planning models for strategic decision-making.
• Collaborate with Program Managers to refine planning assumptions based on execution learnings.
• Review and analyze existing dashboards, models, and data pipelines to understand design patterns and data flows.
• Translate complex data findings into actionable business insights for both technical and non-technical audiences.
• Collaborate with cross-functional teams to ensure data requirements are correctly understood and implemented.

Requirements:

• Strong proficiency in Python for data analysis, statistical modeling, and ML development.
• Ability to build multi-scenario models for scenario planning and what-if analysis.
• Foundational to intermediate experience with ML frameworks and methodologies.
• Proficiency in SQL for querying, joining tables, and data manipulation.
• Understanding of statistical modeling, hypothesis testing, and experimental design.
• Experience in data exploration, cleaning, integration, and anomaly detection.
• Understanding of data modeling concepts and experience with forecasting and prediction models.
• Ability to review existing dashboards, ML models, and reports to understand design patterns and data sources.

Preferred Skills:

• Experience with TensorFlow, PyTorch, neural networks, or deep learning applications.
• Experience with P6 (Primavera), MS Project, or similar project execution systems.
• Familiarity with Azure, AWS, or GCP for data science workflows.
• Experience with SAP, Salesforce, Databricks, or similar ERP/CRM systems.