채용공고 › United Airlines
Data Scientist - Machine Learning
추출된 스킬 11건
| 스킬 | 분류 | 수준 | 근거 문장 (원문) |
|---|---|---|---|
| 머신러닝 | IT·데이터 기술 | 필수 | 4–7+ years of industry experience in AI engineering, data science, machine learning, or applied advanced analytics, including production model deployment. |
| 데이터 웨어하우스 | IT·데이터 기술 | 필수 | Advanced proficiency in Python and SQL, with software engineering best practices including object-oriented programming, Git, and CI/CD; experience architecting data pipelines and working with large datasets in relational or distributed databases such as Snowflake, BigQuery, SQL Server, or Teradata; deep expertise in Generative AI, including prompt engineering, LLM fine-tuning, embeddings, RAG, vec |
| 생성형 AI·LLM | IT·데이터 기술 | 필수 | Advanced proficiency in Python and SQL, with software engineering best practices including object-oriented programming, Git, and CI/CD; experience architecting data pipelines and working with large datasets in relational or distributed databases such as Snowflake, BigQuery, SQL Server, or Teradata; deep expertise in Generative AI, including prompt engineering, LLM fine-tuning, embeddings, RAG, vec |
| CI/CD | IT·데이터 기술 | 필수 | Advanced proficiency in Python and SQL, with software engineering best practices including object-oriented programming, Git, and CI/CD; experience architecting data pipelines and working with large datasets in relational or distributed databases such as Snowflake, BigQuery, SQL Server, or Teradata; deep expertise in Generative AI, including prompt engineering, LLM fine-tuning, embeddings, RAG, vec |
| GCP | IT·데이터 기술 | 필수 | Advanced proficiency in Python and SQL, with software engineering best practices including object-oriented programming, Git, and CI/CD; experience architecting data pipelines and working with large datasets in relational or distributed databases such as Snowflake, BigQuery, SQL Server, or Teradata; deep expertise in Generative AI, including prompt engineering, LLM fine-tuning, embeddings, RAG, vec |
| Python | IT·데이터 기술 | 필수 | Advanced proficiency in Python and SQL, with software engineering best practices including object-oriented programming, Git, and CI/CD; experience architecting data pipelines and working with large datasets in relational or distributed databases such as Snowflake, BigQuery, SQL Server, or Teradata; deep expertise in Generative AI, including prompt engineering, LLM fine-tuning, embeddings, RAG, vec |
| SQL | IT·데이터 기술 | 필수 | Advanced proficiency in Python and SQL, with software engineering best practices including object-oriented programming, Git, and CI/CD; experience architecting data pipelines and working with large datasets in relational or distributed databases such as Snowflake, BigQuery, SQL Server, or Teradata; deep expertise in Generative AI, including prompt engineering, LLM fine-tuning, embeddings, RAG, vec |
| 영어 | 언어 | 필수 | Fluent in written and spoken English. |
| 석·박사 | 학력·법적 자격 | 필수 | Master’s or Ph.D. degree. |
| 고객 경험(CX) | 항공 직무 지식 | 언급 | The Data Scientist designs, develops, and implements scalable AI and Generative AI solutions that improve customer experience, business efficiency, and decision-making. The role builds production-grade applications and workflows using Python, SQL, large language models, Retrieval-Augmented Generation, and agentic AI frameworks. It applies advanced analysis, prompt engineering, evaluation, and obse |
| 이해관계자 관리 | 직무 역량 | 언급 | The Data Scientist designs, develops, and implements scalable AI and Generative AI solutions that improve customer experience, business efficiency, and decision-making. The role builds production-grade applications and workflows using Python, SQL, large language models, Retrieval-Augmented Generation, and agentic AI frameworks. It applies advanced analysis, prompt engineering, evaluation, and obse |
공고 원문
Summary / Purpose
Job overview and responsibilities
The Data Scientist designs, develops, and implements scalable AI and Generative AI solutions that improve customer experience, business efficiency, and decision-making. The role builds production-grade applications and workflows using Python, SQL, large language models, Retrieval-Augmented Generation, and agentic AI frameworks. It applies advanced analysis, prompt engineering, evaluation, and observability practices to deliver reliable and useful AI capabilities. The role partners with cross-functional teams to translate ambiguous business needs into practical solutions and clearly communicate findings and recommendations.
This position is offered on local terms and conditions. Expatriate assignments and sponsorship for employment visas, even on a time-limited visa status, will not be awarded.
Key Responsibilities
- (see Summary / Purpose above — United posts responsibilities embedded in the description narrative rather than as a separate bullet section for this posting)
Minimum Qualifications
- What’s needed to succeed (Minimum Qualifications):
- Master’s or Ph.D. degree.
- Data Science, Statistics, Engineering, Computer Science, Operations Research, or a related STEM field.
- 4–7+ years of industry experience in AI engineering, data science, machine learning, or applied advanced analytics, including production model deployment.
- Advanced proficiency in Python and SQL, with software engineering best practices including object-oriented programming, Git, and CI/CD; experience architecting data pipelines and working with large datasets in relational or distributed databases such as Snowflake, BigQuery, SQL Server, or Teradata; deep expertise in Generative AI, including prompt engineering, LLM fine-tuning, embeddings, RAG, vector databases, and Agentic AI frameworks; hands-on MLOps or LLMOps experience covering model monitoring, latency management, drift mitigation, and system reliability;
- Fluent in written and spoken English.
Preferred Qualifications
- Advanced coursework or specialization in machine learning, artificial intelligence, applied statistics, or cloud computing.
- Experience deploying and scaling enterprise Generative AI applications, particularly multi-agent frameworks or enterprise-scale Retrieval-Augmented Generation.
- Relevant cloud, machine learning, or MLOps certification.
Benefits / Compensation (if stated)
- Not stated in this posting (United's general benefits page cites medical/dental/vision, 401(k), paid time off, and flight privileges)
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