Data Scientist GenAI and Intelligent Automation

Job Description Data Scientist to design, build, and operationalize ML, GenAI, and predictive models that power an enterprise scale AI driven Service Planning & Design (SP&D) platform. The role focuses on cost estimation, calibration, compliance intelligence, and document/image interpretation, working closely with GenAI agents, cloud architects, and domain SMEs. Must Have Technical/Functional Skill Roles & Responsibilities Machine Learning & Predictive Modeling: Design, develop, and tune ML models using XGBoost, Random Forest, scikit-learn and related frameworks. Evaluate model performance using MAE, RMSE, R², and error distribution analysis. GenAI & Agent Driven AI: Collaborate with AI Engineers to embed ML models into GenAI driven, multi-agent workflows. Work with RAG pipelines for document intelligence and contextual Q&A. Enable human-readable explanations for predictions and recommendations. Data Engineering & Feature Development: Analyze structured and unstructured datasets from historical estimates, actual costs, documents, and images. Perform feature engineering from SAP/EES data, historical project attributes, regulatory and standards documentation. Ensure data quality, normalization, and anomaly detection. Image & Non Text Analytics (Preferred): Support AI image analysis use cases: classification and attribute extraction from site photos and drawings, compliance signals against engineering standards, collaborate on pipelines using computer vision outputs and ML inference. MLOps & Model Lifecycle: Support model training, validation, and runtime invocation within cloud-native platforms. Work with DevOps and AI teams on model versioning, reproducibility, monitoring for drift, bias, and performance degradation. Provide inputs for MLOps/LLMOps pipelines and governance dashboards. Required Skills & Experience Strong foundation in Data Science, Machine Learning, and Statistics. Hands‑on experience with Python, scikit-learn, XGBoost, data analysis libraries (NumPy, Pandas). Experience building regression and calibration models. Strong understanding of model evaluation metrics. Experience working with large, complex enterprise datasets. Ability to explain model outputs in business‑friendly language. Preferred Skills Exposure to GenAI/LLM-enabled systems. Experience with RAG pipelines and vector search concepts. Familiarity with computer vision outputs and non‑text data analysis. Experience in utilities, infrastructure, or regulated industries. Understanding of AI governance, explainability, and auditability. Salary Range $160,000-$180,000 a year Employee Benefits Summary Discretionary Annual Incentive. Comprehensive Medical Coverage: Medical & Health, Dental & Vision, Disability Planning & Insurance, Pet Insurance Plans. Family Support: Maternal & Parental Leaves. Insurance Options: Auto & Home Insurance, Identity Theft Protection. Convenience & Professional Growth: Commuter Benefits & Certification & Training Reimbursement. Time Off: Vacation, Time Off, Sick Leave & Holidays. Legal & Financial Assistance: Legal Assistance, 401K Plan, Performance Bonus, College Fund, Student Loan Refinancing. Qualifications Bachelor of Computer Science #J-18808-Ljbffr