Data & Analytics (D&A) Developer II Job ID: 2985

Due to nuclear site access/or export-controlled project requirements, this role requires candidates to be U.S. Citizens and not hold dual citizenship. Candidates must also be willing to work on W2. Hiring: Data Scientist (Operations & Strategy) Location: Greenville, SC (Hybrid) Payrate: $50/hr Required Technical Skills Must Have • Python (Pandas, NumPy, Scikit-learn, SciPy) • Machine Learning • Statistical Analysis • SQL • Data Exploration & Data Cleaning • Data Integration • Forecasting & Predictive Analytics • Scenario Planning & What-If Analysis • Large Language Models (LLMs) • Prompt Engineering • Dashboard & Data Visualization • ETL/Data Pipelines • Data Modeling • Business Intelligence • AI/ML Model Development Nice to Have • TensorFlow or PyTorch • MLflow / MLOps • Azure, AWS, or GCP • Primavera P6 or Microsoft Project • SAP, Salesforce, Databricks • Power BI • Data Governance • RAG (Retrieval-Augmented Generation) • Unit Testing (PyTest) Job Description We are seeking a highly motivated Data Scientist to join our Operations & Strategy team. In this role, you will leverage advanced analytics, machine learning, and AI technologies to transform enterprise data into actionable business insights. You will collaborate with business stakeholders, engineering teams, and data engineers to develop predictive models, optimize operational performance, and support strategic decision-making. This position offers an exciting opportunity to work on enterprise-scale datasets, build AI-powered solutions, and contribute to innovative data-driven initiatives. Key Responsibilities • Analyze large datasets from multiple enterprise systems to identify trends, patterns, and business opportunities. • Develop machine learning models for forecasting, predictive analytics, and scenario planning. • Design and implement data pipelines for automated reporting and model deployment. • Build scenario planning models to evaluate business assumptions and "what-if" analyses. • Perform statistical analysis and validate model performance using industry best practices. • Work with cross-functional teams to define data requirements and improve data quality. • Utilize Large Language Models (LLMs) and prompt engineering to develop AI-powered business solutions. • Create executive dashboards and performance reports that support operational decision-making. • Review existing dashboards, SQL queries, and analytical models to identify enhancement opportunities. • Collaborate with data engineers to improve enterprise data infrastructure and reporting capabilities. • Document analytical processes, model methodologies, and technical findings. • Present complex analytical insights to both technical and non-technical stakeholders. Qualifications • Bachelor's or Master's degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, or a related field. • Strong experience with Python for data analysis and machine learning. • Solid understanding of SQL, statistical modeling, and predictive analytics. • Experience working with large enterprise datasets. • Knowledge of machine learning frameworks and model evaluation techniques. • Experience with data visualization and dashboard development. • Strong analytical, problem-solving, and communication skills. • Ability to work collaboratively with cross-functional teams in a dynamic environment. • Passion for AI, data science, and continuous learning. Preferred Experience • Experience with cloud platforms (Azure, AWS, or GCP). • Familiarity with enterprise systems such as SAP, Salesforce, Databricks, or similar platforms. • Knowledge of Primavera P6 or project management systems. • Experience with MLOps, model deployment, and experiment tracking. • Exposure to advanced AI applications, including Retrieval-Augmented Generation (RAG).