Sportradar
Senior Software Engineer, Data(m/w/x)
Full-timeWith HomeofficeSenior
Wien
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SPSportradar
Senior Data Scientist(m/w/x)
Wien
Full-timeWith Home OfficeSenior
AI/ML
Data Science
Nejo AI Summary
Designing scalable audience data models and ETL pipelines with PySpark for a global sports technology company. 3+ years analytics engineering or data engineering experience required. Flexible working hours, vibrant community.
Requirements
- 3+ years Analytics Engineering, Data Engineering, or related field experience
- Excellent SQL and Python skills
- Infrastructure as Code (Terraform) experience
- Strong proficiency building ETL pipelines, ideally with PySpark
- Solid logical and physical data modelling experience for audience/behavioural datasets
- Git or similar version control tools proficiency
- Cloud-based services experience, preferably AWS
- High attention to detail and data quality commitment
- Strong communication and stakeholder partnering skills
- Fluent English
- Data visualisation tools and stakeholder dashboard building experience
- AdTech and audience activation ecosystems experience
- ML technologies and production ML pipelines experience
- Knowledge of testing strategies like TDD
- Identity graphs, segmentation frameworks, or CDPs experience
- CI/CD workflows creation and maintenance experience
- English language proficiency
Tasks
- Interpret audience and campaign data
- Guide strategic decisions with insights
- Design scalable audience data models
- Support segmentation, activation, and measurement
- Build and maintain data models
- Develop data-driven systems
- Focus on quality, observability, and security
- Evaluate existing data sources
- Monitor audience-related products
- Ensure data integrity and reliability
- Conduct regular QA checks
- Collaborate with sales, tech, product, and ML teams
- Design advanced audience dashboards
- Implement activation frameworks
- Refine audience solutions
- Drive evaluation of audience-focused solutions
- Support ML and AI initiatives
- Create measurable value for clients
Work Experience
- 3 years
Education
- Master's degree
Languages
- English – Fluent
Tools & Technologies
- SQL
- Python
- Terraform
- PySpark
- Git
- AWS
- ML technologies
- CI/CD
Benefits
Flexible Working
- Flexible working hours
Informal Culture
- Collaborative environment
- Vibrant and inclusive community
Team Events
- Social events
- Teambuilding
Other Benefits
- Women in Tech group
- Pride group
- Reulay app
Mental Health Support
- Global Employee Assistance Programme
- Calm app
Learning & Development
- Online training videos
Find the original job posting in its most current version here. Nejo automatically captured this job from the website of Sportradar 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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SPSportradar
Senior Data Scientist(m/w/x)
Wien
Full-timeWith Home OfficeSenior
AI/ML
Data Science
Nejo AI Summary
Designing scalable audience data models and ETL pipelines with PySpark for a global sports technology company. 3+ years analytics engineering or data engineering experience required. Flexible working hours, vibrant community.
Requirements
- 3+ years Analytics Engineering, Data Engineering, or related field experience
- Excellent SQL and Python skills
- Infrastructure as Code (Terraform) experience
- Strong proficiency building ETL pipelines, ideally with PySpark
- Solid logical and physical data modelling experience for audience/behavioural datasets
- Git or similar version control tools proficiency
- Cloud-based services experience, preferably AWS
- High attention to detail and data quality commitment
- Strong communication and stakeholder partnering skills
- Fluent English
- Data visualisation tools and stakeholder dashboard building experience
- AdTech and audience activation ecosystems experience
- ML technologies and production ML pipelines experience
- Knowledge of testing strategies like TDD
- Identity graphs, segmentation frameworks, or CDPs experience
- CI/CD workflows creation and maintenance experience
- English language proficiency
Tasks
- Interpret audience and campaign data
- Guide strategic decisions with insights
- Design scalable audience data models
- Support segmentation, activation, and measurement
- Build and maintain data models
- Develop data-driven systems
- Focus on quality, observability, and security
- Evaluate existing data sources
- Monitor audience-related products
- Ensure data integrity and reliability
- Conduct regular QA checks
- Collaborate with sales, tech, product, and ML teams
- Design advanced audience dashboards
- Implement activation frameworks
- Refine audience solutions
- Drive evaluation of audience-focused solutions
- Support ML and AI initiatives
- Create measurable value for clients
Work Experience
- 3 years
Education
- Master's degree
Languages
- English – Fluent
Tools & Technologies
- SQL
- Python
- Terraform
- PySpark
- Git
- AWS
- ML technologies
- CI/CD
Benefits
Flexible Working
- Flexible working hours
Informal Culture
- Collaborative environment
- Vibrant and inclusive community
Team Events
- Social events
- Teambuilding
Other Benefits
- Women in Tech group
- Pride group
- Reulay app
Mental Health Support
- Global Employee Assistance Programme
- Calm app
Learning & Development
- Online training videos
Find the original job posting in its most current version here. Nejo automatically captured this job from the website of Sportradar 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.
About the Company
Sportradar
Industry
Media
Description
The company is a worldwide leader in sports data and audiovisual services for bookmakers, offering data-driven marketing services for betting operators.
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