SAP
Applied Senior/Staff Scientist with SAP S/4 Domain Expertise(m/w/x)
Full-timeWith HomeofficeSenior
Berlin, Garching bei München
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SASAP
Data Science Manager: ABAP Foundation Model(m/w/x)
Berlin
Full-timeWith Home OfficeManagement
Nejo AI Summary
Overseeing development and fine-tuning of large language models for enterprise cloud transformation at software provider for 400k+ customers. 2+ years managing data science teams and 1+ years fine-tuning large language models required. Focus on cutting-edge LLM development.
Requirements
- Advanced degree in Computer Science, Data Science, Machine Learning, or related field
- Strong expertise in data science, machine learning algorithms, and NLP
- 10+ years of related professional experience
- 2+ years experience in managing and leading data science teams
- 1+ years of experience working with fine tuning LLM models
- Experience finetuning LLMs for Code Generation
- Demonstrated ability to inspire, mentor, and develop high-performing teams
- Exceptional comfort with ambiguity and bias toward iterative action
- Excellent verbal and written communication skills
- Experience working with cross-functional teams and managing research collaborations
Tasks
- Lead a diverse team of data scientists and data engineers
- Oversee the development and fine-tuning of foundation models
- Deliver foundation models to enhance SAP customers' cloud transformation
- Ensure alignment of team objectives with broader ABAP Foundation Model goals
- Coordinate with various stakeholders within SAP
Work Experience
- 10 years
Education
- Master's degree
Languages
- English – Business Fluent
Find the original job posting in its most current version here. Nejo automatically captured this job from the website of SAP and processed the information on Nejo with the help of AI for you. Despite careful analysis, some information may be incomplete or inaccurate. Please always verify all details in the original posting! Content and copyrights of the original posting belong to the advertising company.
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SASAP
Data Science Manager: ABAP Foundation Model(m/w/x)
Berlin
Full-timeWith Home OfficeManagement
Nejo AI Summary
Overseeing development and fine-tuning of large language models for enterprise cloud transformation at software provider for 400k+ customers. 2+ years managing data science teams and 1+ years fine-tuning large language models required. Focus on cutting-edge LLM development.
Requirements
- Advanced degree in Computer Science, Data Science, Machine Learning, or related field
- Strong expertise in data science, machine learning algorithms, and NLP
- 10+ years of related professional experience
- 2+ years experience in managing and leading data science teams
- 1+ years of experience working with fine tuning LLM models
- Experience finetuning LLMs for Code Generation
- Demonstrated ability to inspire, mentor, and develop high-performing teams
- Exceptional comfort with ambiguity and bias toward iterative action
- Excellent verbal and written communication skills
- Experience working with cross-functional teams and managing research collaborations
Tasks
- Lead a diverse team of data scientists and data engineers
- Oversee the development and fine-tuning of foundation models
- Deliver foundation models to enhance SAP customers' cloud transformation
- Ensure alignment of team objectives with broader ABAP Foundation Model goals
- Coordinate with various stakeholders within SAP
Work Experience
- 10 years
Education
- Master's degree
Languages
- English – Business Fluent
Find the original job posting in its most current version here. Nejo automatically captured this job from the website of SAP and processed the information on Nejo with the help of AI for you. Despite careful analysis, some information may be incomplete or inaccurate. Please always verify all details in the original posting! Content and copyrights of the original posting belong to the advertising company.
Like this job?
BetaYour Career Agent finds similar jobs for you every day.
About the Company
SAP
Industry
IT
Description
SAP innovations help over four hundred thousand customers worldwide work together more efficiently and use business insight more effectively.
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