Cricket Data Scientist & Data Engineer (Hybrid)

CricViz; Greater London; Hybride; GBP 65 000 - 90 000; Plein temps

Avantages offerts par ce poste

Hybrid working

25 days' annual leave + bank holidays

Pension

Life insurance

Professional development

Résumé du poste

CricViz in London, UK, invites applications for a Data Scientist / Data Engineer to build advanced cricket metrics, predictive models and data pipelines from tracking data. The role blends performance analytics with media, fantasy and betting analytics.

You will develop models, validate them, deploy into production, and collaborate with Product, Engineering and Broadcast teams. A Math/Data Science/CS degree and ~2 years' experience with Python/SQL are expected; familiarity with pandas, NumPy,

Qualifications

• Degree in Mathematics, Data Science, Computer Science, Statistics or related discipline.
• Approximately 2 years' professional experience in data science or data engineering.
• Strong Python and SQL skills.
• Experience with pandas, NumPy, scikit-learn or similar tools.

Responsabilités

• Develop cricket performance metrics and predictive models.
• Build and optimise data pipelines using tracking data.
• Validate models and integrate them into production systems.
• Deliver bespoke analysis and datasets for professional clients.
• Collaborate with Product, Engineering and Broadcast teams.

Connaissances

Python

SQL

Data analysis

Machine learning

Formation

Degree in Mathematics/Data Science/CS/Statistics

Outils

pandas

NumPy

scikit-learn

Description du poste

CricViz in London, UK, invites applications for a Data Scientist / Data Engineer to build advanced cricket metrics, predictive models and data pipelines from tracking data. The role blends performance analytics with media, fantasy and betting analytics.

You will develop models, validate them, deploy into production, and collaborate with Product, Engineering and Broadcast teams. A Math/Data Science/CS degree and ~2 years' experience with Python/SQL are expected; familiarity with pandas, NumPy,