We are seeking a skilled Data Science Engineer to design, build, and deploy production machine learning solutions for an enterprise Fleet Cascading & Optimization Platform managing 46,000+ vehicles across 545+ locations. In this role, you will develop and operationalize demand forecasting, cascading optimization, contract intelligence (NLP/Vision), and out-of-spec prediction models with a strong focus on explainability and business impact. You will own the end-to-end ML lifecycle — from experimentation and model development to scalable production deployment on AWS—working closely with engineering and business stakeholders to deliver reliable, data-driven outcomes.

Must-Have Requirements
- Programming & ML Frameworks: Python; PyTorch or TensorFlow; scikit-learn; XGBoost or LightGBM; pandas; NumPy
- Time Series & Forecasting: BSTS; Prophet; Temporal Fusion Transformer (TFT); hierarchical forecasting with MinT reconciliation
- Optimization: Linear Programming and MILP using tools such as PuLP and OR-Tools; constraint satisfaction; min-cost flow optimization
- AWS ML Stack:



Amazon SageMaker (Training Jobs, Endpoints, Model Monitor, Clarify, Feature Store, Pipelines)

Nice-to-have
- NLP & Document AI: Amazon Textract; LayoutLMv3; Retrieval-Augmented Generation (RAG) pipelines; Amazon Bedrock (Claude); OpenSearch vector databases
- Advanced Machine Learning: Graph Neural Networks (GNNs); Deep Reinforcement Learning; Survival Analysis (Cox Proportional Hazards, XGBoost-Survival); attention-based models
- Explainability & MLOps: SHAP, LIME, Captum; MLflow; A/B testing; champion/challenger frameworks; model and data drift detection

Core Responsibilities
- Build demand forecasting models (XGBoost, BSTS, Temporal Fusion Transformer) with hierarchical reconciliation across 545+ locations
- Develop cascading optimization using MILP/Min-Cost Flow solvers (PuLP, OR-Tools, Gurobi) and Hybrid ML+Optimization pipelines
- Implement document intelligence pipeline: Textract + LayoutLM

📌 Senior Data Science Engineer (Valencia)
🏢 Trinetix
📍 Valencia