Data & Analytics (D&A) Developer II

We are seeking a Data & Analytics (D&A) Developer II to join our client's Engineering Operations & Strategy team supporting Gas Turbine programs. In this role, you will leverage data analytics, machine learning, and AI to improve operational planning, forecasting, and business decision-making across global engineering programs., * Analyze data from enterprise systems such as SAP, Salesforce, Databricks, Power BI, and other business platforms.

• Develop machine learning models for forecasting, scenario planning, and predictive analytics.
• Build and maintain Python-based data pipelines and ETL processes.
• Perform data exploration, cleansing, validation, and anomaly detection.
• Design scenario planning models to evaluate business assumptions and support strategic decision-making.
• Create executive dashboards, KPIs, and reporting solutions that provide actionable insights.
• Collaborate with Data Engineers, Program Managers, and Operations teams to define business requirements and optimize data solutions.
• Utilize Large Language Models (LLMs) and prompt engineering techniques to improve workflows and business processes.
• Document analytical methods, model performance, and business logic to ensure transparency and reproducibility.

The ideal candidate has strong Python and SQL skills, experience working with enterprise data, and a passion for solving complex business problems through data-driven solutions. You will collaborate with engineering, operations, and IT teams to build predictive models, develop automated data pipelines, and deliver actionable insights through dashboards and reporting., * Bachelor's degree in Computer Science, Data Science, Engineering, Mathematics, Statistics, or a related field (or equivalent experience).

• Strong experience with Python, including Pandas, NumPy, Scikit-learn, and statistical analysis libraries.
• Proficiency in SQL, including complex queries, joins, and data manipulation.
• Experience with machine learning, predictive modeling, and model evaluation.
• Strong understanding of data cleansing, integration, and exploratory data analysis.
• Experience working with large enterprise datasets and multiple data sources.
• Knowledge of forecasting, scenario planning, and statistical modeling.
• Familiarity with Large Language Models (LLMs) and prompt engineering.
• Excellent analytical, communication, and problem-solving skills., * Experience with TensorFlow, PyTorch, or other deep learning frameworks.
• Knowledge of MLflow, MLOps, or model deployment practices.
• Experience with Azure, AWS, or Google Cloud Platform.
• Familiarity with Primavera P6, MS Project, or project execution systems.
• Experience with SAP, Salesforce, Databricks, or other ERP/CRM platforms.
• Knowledge of Retrieval-Augmented Generation (RAG), AI agents, or advanced LLM applications.
• Understanding of data governance and responsible AI practices.

3.73.7 out of 5 stars Greenville, SC 29615 Hybrid work $47 - $52 an hour - Contract