At a Glance
- Tasks: Analyse data to enhance sports technology and improve business decisions.
- Company: Join Sportradar, a leader in sports technology and analytics.
- Benefits: Competitive salary, professional development, and global team collaboration.
- Other info: Work in a dynamic environment with international colleagues.
- Why this job: Make an impact in the sports industry with your data skills.
- Qualifications: Experience in data management and proficiency in BI tools required.
The predicted salary is between 39600 - 48400 £ per year.
Описание
Sportradar is a sports technology company operating at the intersection of sports, media, and betting.
Its technology and expertise support more than 1,700 sports federations, media outlets, betting operators, and consumer platforms across 120 countries.
- Задачи
- Analyze stakeholder requirements and opportunities to improve business decisions and operational efficiency through data analytics
- Deliver data analytics and reporting solutions using commercial, operational, and business data
- Develop data models for reporting and analytics
- Develop and deploy data visualizations and reports for management and internal business partners
- Present ideas and solutions clearly to business and technical stakeholders
- Document requirements and follow data governance protocols
- Support the design and development of scalable, reliable, and secure data warehousing architectures and data integration and processing pipelines
- Train and empower business users to use business intelligence tools and analytics solutions
- Propose innovative ways to use data to improve product and service monetization, acquire new sports rights, and analyze commercial strategies
- Co-create and deliver a business intelligence roadmap with business and technical stakeholders across the Sportradar group
- Create and maintain technical documentation for BI tools
- Design, create, and implement the reporting layer
- Improve and expand existing reporting interfaces
- Требования
- Demonstrated technical expertise in business intelligence tools, dashboard and reporting application development, databases, data modelling, and ETL processes
- Hands-on experience developing software or analytics solutions
- At least 3 years of experience in data management and/or business intelligence projects
- Proficiency with relational databases and advanced SQL knowledge
- Experience with BI tools such as Qlik Sense/Qlik View, Tableau, Power BI, or equivalent
- Bachelor’s degree in Computer Science, Engineering, Mathematics, Statistics, Economics, or a related field; equivalent experience is acceptable
- Fluent English, written and spoken
- Autonomous, rigorous, creative, and a team player
- Nice to have: experience with Microsoft SQL Server, Amazon Redshift, and/or Amazon Athena, predictive analytics, statistical modelling, or machine learning
- Условия
- Competitive salary and benefits
- Investment in continued professional development
- International team collaboration with colleagues from around the world
- #J-18808-Ljbffr
data analyst in sports technology employer: Enfint
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We think this is how you could land data analyst in sports technology
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We think you need these skills to ace data analyst in sports technology
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
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How to prepare for a job interview at Enfint
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
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Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
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✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
