Senior Full-Stack Data Scientist | ML/AI, Hybrid

Clearscoretechnologylimited; Greater London; Híbrido; GBP 90.000 - 130.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Paid holidays

Hybrid work

Health cover

Pension

Descripción de la vacante

ClearScore is seeking a Senior Full Stack Data Scientist to join the Data & Analytics team. You will own end-to-end data science and ML solutions across targeting use cases, collaborating with cross-functional partners to drive user-centric outcomes.

You will stay at the forefront of ML/AI, exploring Foundation Models and production-ready deployments, while helping shape data and model quality. The role offers a hybrid work environment and opportunities across markets.

Formación

• Advanced Python and SQL skills, and a strong understanding of dbt and Analytics Engineering for feature engineering.
• In-depth knowledge of varied statistical and machine learning techniques.
• Capable across the full model lifecycle, including deployment and maintenance in production environments.

Responsabilidades

• Lead end-to-end development of data science and ML solutions from business concept through impact evaluation.
• Collaborate with cross-functional stakeholders to shape how Data Science supports business needs.
• Stay at the cutting edge of ML/AI developments and test them against production systems.
• Drive improvements and standardise model development and deployment processes.
• Utilise model outputs to inform decision-making within the Global Targeting squad.

Conocimientos

Python

SQL

dbt

Analytics Engineering

Machine learning

Educación

Postgraduate degree in STEM

Herramientas

Databricks

Descripción del empleo

ClearScore is seeking a Senior Full Stack Data Scientist to join the Data & Analytics team. You will own end-to-end data science and ML solutions across targeting use cases, collaborating with cross-functional partners to drive user-centric outcomes.

You will stay at the forefront of ML/AI, exploring Foundation Models and production-ready deployments, while helping shape data and model quality. The role offers a hybrid work environment and opportunities across markets.