Senior Data Scientist

🔥 18 hours ago

🇨🇴 Colombia – Remote

⏰ Full Time

🟠 Senior

📊 Data Scientist

👻 Ghost score 18%

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Capgemini

WebsiteLinkedInAll Job Openings

10,000+ employees

Founded 1967

💼 Consulting

🏥 Healthcare

📦 Logistics

Consulting • Healthcare • Logistics

Capgemini is a global leader in partnering with businesses to transform and manage their operations by harnessing the power of technology. With expertise across a wide array of industries such as aerospace, automotive, banking, and healthcare, Capgemini provides a constantly evolving portfolio of services to meet the ever-changing needs of their clients. Their offerings include cloud, cybersecurity, data and artificial intelligence, and enterprise management, among others. Capgemini also emphasizes innovation and sustainability, helping companies achieve digital transformation while promoting environmental and social responsibility. Additionally, Capgemini provides career opportunities across various levels and professions, encouraging innovation and diversity in its workforce.

📋 Description

• 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

• 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

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