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Analyst - Data Scientist

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Deadline: 23/08/2026

Skills for this role

Skills we detected for this role.

  • Python
  • SQL
  • Git
  • Machine Learning
  • Excel
  • Generative AI
  • Snowflake
  • BigQuery
  • Prompt Engineering
  • Statistics
  • Data Analysis

Opportunity brief

United Airlines is hiring for the role of Analyst - Data Scientist!

Responsibilities of the Candidate:

  • Design, develop, test, and deploy robust AI and Generative AI solutions that improve customer experience, operational efficiency, and business decision-making.
  • Build and deploy production-grade workflows, applications, and data pipelines using Python, SQL, relational databases, and modern AI tools.
  • Perform advanced exploratory analysis and feature engineering across structured and unstructured datasets to support scalable AI and Generative AI use cases.

- Implement prompt engineering strategies, conduct LLM experiments, and apply output evaluation frameworks to ensure quality, relevance, accuracy, safety, and business usefulness.

  • Develop and scale Retrieval-Augmented Generation pipelines and integrate agentic AI frameworks for multi-step reasoning and workflow automation.
  • Implement AI observability and MLOps practices to monitor model behavior and system reliability; collaborate with cross-functional teams and communicate findings, risks, and recommendations to stakeholders.

Requirements:

  • Bachelor's degree required
  • Implement AI observability and MLOps practices to monitor model behavior and system reliability; collaborate with cross-functional teams and communicate findings, risks, and recommendations to stakeholders.
  • 1–2 years of industry experience in AI engineering, data science, analytics, or machine learning, including practical experience moving models or analytical workflows toward production.

- Strong Python and SQL proficiency; software engineering fundamentals, including Git; experience with large relational datasets and platforms such as Microsoft SQL Server, Snowflake, BigQuery, or Teradata; practical knowledge of LLMs, prompt engineering, embeddings, RAG, and agentic AI; AI observability and MLOps; strong analytical problem-solving; ability to create clear Excel and PowerPoint presentations; strong interpersonal, written, and verbal communication skills.

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