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Capgemini

Senior Data Scientist

Capgemini

. Develop and work with core machine learning solutions .

Posted 11/3/2026full-timeRemote • ColombiaSeniorWebsite

Core Competencies

Role fit
Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in developing and deploying machine learning solutions, particularly in forecasting and classification models using XGBoost and LightGBM. Proficient in SQL, Python, and agentic coding with Claude Code, Codex, or Cursor, while effectively communicating complex model insights to non-technical stakeholders.

Highest-signal resume keywords
Machine Learning Solutions DevelopmentXGBoost And/Or LightGBM In ProductionStrong SQL SkillsAgentic Coding With Claude Code, Codex, Or CursorLLM APIs At Scale

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills
Machine LearningForecasting ModelsClassification ModelsSQLPythonPySparkXGBoostLightGBMSHAPAgentic Coding
Soft Skills
Communication With Non-Technical Stakeholders
Tools & Technologies
AzureDatabricksGCP/VertexAWS/SageMakerLLM APIs
Industry Keywords
GenAI ProductsRAGVector SearchBatch JobsAsync Jobs

Tech Stack

Tools & technologies
AWSAzureGoogle Cloud PlatformPySparkPythonSQL

About the role

Key responsibilities & impact
  • Develop and work with core machine learning solutions
  • Build and deploy forecasting and classification models
  • Use XGBoost and/or LightGBM in production
  • Explain and debug models with SHAP for non-technical stakeholders
  • Build GenAI products involving RAG, vector search, and agents with tool use
  • Implement agentic coding using Claude Code, Codex, or Cursor
  • Run LLM API batch or async jobs at scale
  • Work with Azure, Databricks, GCP/Vertex, or AWS/SageMaker platforms

Requirements

What you’ll need
  • Strong SQL, including complex joins, CTEs, window functions, and query performance tuning
  • Strong Python
  • PySpark or similar
  • Real forecasting and classification work in production or serious projects; coursework does not count
  • XGBoost and/or LightGBM in production
  • SHAP for explaining and debugging models for non-technical stakeholders
  • Hands-on agentic coding with Claude Code, Codex, or Cursor
  • Built GenAI products, including RAG, vector search, and agents with tool use
  • LLM APIs at scale, using batch or async jobs with thousands of calls
  • Azure and/or Databricks preferred; strong GCP/Vertex or AWS/SageMaker experience acceptable