Data Scientist - Ciudad de México

Job summary

ETAP empowers customers to make informed decisions throughout the life cycle of their projects with innovative software solutions for electrical systems. By applying ETAP solutions, customers experience continuous intelligence during design and engineering and into operations and maintenance using a unified electrical digital twin platform. ETAP supports customers in their digital transformation and sustainable energy transitions for a green and smart future, helping them to prioritize safety, maximize reliability, and stay resilient.

Responsibilities

• Build and deploy machine learning models for classification, regression, ranking, and recommendation tasks.
• Apply feature engineering, cross-validation, and model evaluation techniques to improve accuracy and robustness.
• Develop and maintain reproducible workflows using Python, SQL, MLflow/W&B, and Azure ML.
• Collaborate with engineering teams to deliver models as scalable APIs using FastAPI and Docker.
• Monitor and evaluate models in production to detect drift, maintain quality, and ensure reliability.

Qualifications

• Strong programming skills in Python with proficiency in Pandas, NumPy, and scikit-learn.
• Experience with SQL/NoSQL databases and data pipelines.
• Hands-on knowledge of XGBoost / LightGBM for tabular modeling.
• Experience with model deployment and tracking using Git, Docker, FastAPI, and Azure ML.
• Solid understanding of evaluation metrics for classification, regression, and ranking.

Desired requirements

• Experience with PyTorch / TensorFlow, Optuna, and ONNX.
• Exposure to Graph ML (PyTorch Geometric, DGL) or Generative AI workflows (embeddings, RAG, LangChain/LlamaIndex).
• Strong communication skills, able to explain technical concepts to varied audiences.

Descripción del trabajo