Must Have Technical/Functional Skill
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.
Roles & Responsibilities
Key Responsibilities
Machine Learning & Predictive Modeling
- Design and develop ML models
- Build and tune models using XGBoost, Random Forest, scikit learn, and related frameworks
- Evaluate model performance using MAE, RMSE, R , 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:
o SAP/EES data
o Historical project attributes
o Regulatory and standards documentation
- Ensure data quality, normalization, and anomaly detection
Image & Non Text Analytics (Preferred)
- Support AI image analysis use cases:
o Classification and attribute extraction from site photos and drawings
o 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:
o Model versioning and reproducibility
o 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:
o Python
o scikit learn, XGBoost
o Data analysis libraries (NumPy, Pandas)
- Experience building regression and calibrati on 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
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