Senior Data Scientist - Decisioning and Optimisation

GlobalLogic Inc.; Greater London; Híbrido; GBP 90.000 - 140.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Hybrid work model

Private healthcare

Gym discounts

Annual volunteering day

Descripción de la vacante

GlobalLogic is seeking a Data Scientist to direct design, development and productionization of an enterprise decisioning and optimization platform in London. You will own advanced causal modeling, uplift strategies, and campaign economics within a Databricks-based environment.

Role requires expert Python and SQL, production ML experience, and proficiency with Databricks tools such as Unity Catalog, Delta Lake and MLflow.

Formación

• Expert-level Python for end-to-end data science and production ML.
• Advanced SQL for querying complex datasets (customers, transactions, campaigns).
• Production ML on Databricks with notebooks, Delta Lake, and model registry.
• Proficient in Git workflows, CI/CD, unit testing, and reproducible deployments.
• Understanding uplift modeling and constrained optimization.

Responsabilidades

• Lead design, experimentation, and deployment of customer decisioning and uplift models.
• Develop optimization models balancing campaign economics and budgets.
• Build production ML pipelines on Databricks with Unity Catalog and scheduled scoring.
• Enforce Git workflows, PR reviews, automated tests, and Azure DevOps releases.
• Implement end-to-end MLOps: monitoring, logging, drift detection, handover.
• Collaborate with engineers and stakeholders to translate economics into rules.

Conocimientos

Python

SQL

PySpark

Databricks

ML in production

Git workflows

Azure DevOps

Unit testing

MLOps

uplift modeling

Herramientas

Databricks

Unity Catalog

Delta Lake

MLflow

Azure DevOps

Descripción del empleo

GlobalLogic is seeking a Data Scientist to direct design, development and productionization of an enterprise decisioning and optimization platform in London. You will own advanced causal modeling, uplift strategies, and campaign economics within a Databricks-based environment.

Role requires expert Python and SQL, production ML experience, and proficiency with Databricks tools such as Unity Catalog, Delta Lake and MLflow.