Data Scientist (D&A Developer II)

Contract Data Scientist role supporting GE Vernova’s HDPE Operations & Strategy with Python/SQL analytics and machine learning for harmonized insights and scenario planning.

Responsibilities

• Contribute to an engineering vision that advances how data intelligence and AI-powered tools are used to manage, predict, and operate across GE Vernova’s global business.
• Bridge Engineering domain data knowledge, business planning, operations, and IT execution teams to define needed data, how it should be structured, and which AI/ML solutions create the most value.
• Support centralized business operations and program reporting by delivering harmonized insights and predicted outcome ranges to business stakeholders worldwide.
• Build scenario planning models to test critical business assumptions.
• Track project execution using Primavera P6 and enterprise systems.
• Identify gaps between planned and actual performance to support proactive decision-making.
• Review existing dashboards, machine learning models, and reports to understand design and implementation.

Requirements

• Strong data analysis, statistical modeling, and ML development experience using pandas, NumPy, scikit-learn, SciPy, curve fitting, and object-oriented programming.
• Ability to build multi-scenario models for assumption testing and comparison of alternative planning outcomes.
• Foundational to intermediate experience with ML frameworks and methods such as scikit-learn, XGBoost, or similar tools.
• Understanding of model validation metrics including R², MAE, RMSE, cross-validation, and custom scoring functions.
• Proficiency with SQL query, join, data manipulation, and interpretation of complex SQL queries.
• Understanding of statistical modeling, hypothesis testing, and experimental design.
• Ability to independently explore enterprise datasets and identify patterns, gaps, and opportunities.
• Experience working with messy datasets, handling inconsistencies, and standardizing formats across heterogeneous systems.
• Experience merging datasets from enterprise sources including SAP, Salesforce, Databricks, and ERP/CRM platforms.
• Ability to identify outliers, errors, and unusual patterns across structured and unstructured data.
• Understanding of data modeling concepts across heterogeneous systems.
• Experience developing models for scenario planning, forecasting, and predictive use cases.
• Familiarity with LLMs and basic prompt engineering techniques for practical business applications.
• Ability to review existing dashboards, ML models, and reports to understand design.

Technologies

• Python, pandas, NumPy, scikit-learn, SciPy, XGBoost
• SQL
• R², MAE, RMSE, cross-validation
• LLMs
• Primavera P6
• SAP, Salesforce, Databricks

Location

• Hybrid remote in Atlanta, GA 30308

Pay

• $55/hour on W2
• $55.00 per hour

Expected Hours

• 40.0 hours/week