Junior Data Scientist - Hybrid, 6-Month Telecoms Contract

Advanced Resource Managers Ltd; Slough; Hybride; GBP 57 000 - 75 000; Plein temps

Résumé du poste

Advanced Resource Managers Ltd is seeking a Junior Data Scientist for a 6-month contract in Slough with hybrid working (2–3 days onsite). The role focuses on hands-on data science to improve customer experience, stock management models, and marketing effectiveness.

You will build models in the cloud, explore data, and collaborate with stakeholders to drive strategic decisions. Key activities include developing and validating basic models, maintaining data pipelines, and applying statistical

Qualifications

• Proficient in SQL, Python and ML tooling.
• Experience with data pipelines and data wrangling.
• Knowledge of ML lifecycle from development to deployment.
• Experience with model validation, monitoring and versioning.

Responsabilités

• Build, validate, optimise and manage basic models and data pipelines.
• Handle parts of the data science lifecycle including documentation and security considerations.
• Analyze data using statistical methods to improve customer experience and business results.
• Identify improvements in own work and develop skills.
• Work with internal datasets and collaborate with the data science team to share knowledge.
• Collaborate with project groups to achieve the best outcomes.

Connaissances

SQL

Python

scikit-learn

PySpark

Database experience

Code testing

ML lifecycle

Model deployment

Data validation

Model versioning

Model monitoring

Communication

Stakeholder management

Outils

Git

Description du poste

Advanced Resource Managers Ltd is seeking a Junior Data Scientist for a 6-month contract in Slough with hybrid working (2–3 days onsite). The role focuses on hands-on data science to improve customer experience, stock management models, and marketing effectiveness.

You will build models in the cloud, explore data, and collaborate with stakeholders to drive strategic decisions. Key activities include developing and validating basic models, maintaining data pipelines, and applying statistical