GenAI Data Scientist: Forecasting & Platforms

Capgemini Engineering; Bogotá; On-site; COP 120,000,000 - 190,000,000; Full time

Job summary

Capgemini Engineering in Bogotá seeks an experienced ML engineer to join our data science practice. You will design, build, and deploy models for forecasting and classification across client projects, with emphasis on GenAI and scalable architectures.

You will work with Azure Databricks, GCP or AWS, and collaborate with engineers and business stakeholders to translate analytics into measurable outcomes. If you thrive in a fast-paced, global team, this is for you.

Qualifications

• Strong SQL with complex joins, CTEs, window functions and tuning.
• Strong Python and PySpark or similar.
• Experience with real forecasting and classification (demand forecasts, lead scoring).
• Experience with XGBoost and/or LightGBM in production.
• Experience explaining models with SHAP to non-technical stakeholders.
• Hands-on GenAI coding with Claude Code, Codex, or Cursor.
• Built GenAI products: RAG, vector search, agents with tool use.
• Experience with LLM APIs at scale (batch/async).
• Cloud/platform: Azure and/or Databricks; strong GCP Vertex or AWS/SageMaker.

Responsibilities

• Develop and productionize ML models for forecasting and classification.
• Implement GenAI solutions with RAG, vector search and tool-using agents.
• Collaborate with data engineers to ensure data quality and model deployment.
• Explain model decisions to non-technical stakeholders using SHAP.
• Monitor model performance and iterate with stakeholders.

Skills

SQL

Python

PySpark

XGBoost/LightGBM

SHAP explanations

Tools

Azure Databricks

GCP Vertex / AWS SageMaker

Claude Code

Codex

Cursor

LLM APIs at scale

Vector search

Job description

Capgemini Engineering in Bogotá seeks an experienced ML engineer to join our data science practice. You will design, build, and deploy models for forecasting and classification across client projects, with emphasis on GenAI and scalable architectures.

You will work with Azure Databricks, GCP or AWS, and collaborate with engineers and business stakeholders to translate analytics into measurable outcomes. If you thrive in a fast-paced, global team, this is for you.