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# Data Scientist

- **Company:** TalentHub Global Ltd
- **Location:** London, UK
- **Experience:** Expert
- **Salary:** £70,000.0 - £80,000.0
- **Contract:** Temporary contract
- **Skills:** Airflow, Business Analytics Applications, Build Automation, Big Data, BigQuery, Cloud Computing, Apache Hadoop, Python (Programming Language), Machine Learning, Open Source Technology, Tensorflow, Software Engineering, Pytorch, Jupyter, Pandas, Pyspark, Scikit Learn, Stream Processing
- **Published:** June 13, 2026
- **Apply:** https://uk.indeed.com/viewjob?jk=3032d7d17385a1b0

## About the Role

* Strong Big Data ( BigQuery, Hadoop and PySpark)
 * Python & applied ML (pandas, scikit-learn, PyTorch/TensorFlow)
 * Cloud experience (GCP), real-time data processing & ML inference pipelines
 * Production-grade software development discipline & clean, testable code
 * Open-source tooling (Jupyter, Airflow, vector databases)
 * Strong stakeholder consulting and communication skills

## Description

We're working with one of the world's largest banking and financial services organisations, a global name with operations across 50+ countries, to find exceptional Data Scientists. This is a rare opportunity to own end-to-end ML delivery at real scale, with genuine business impact.

You will work directly with a consultancy on site on a 12 month fixed term contract (with strong opportunities to stay with the business further).

The role

You'll join a data & analytics function at the heart of the UK business, building production-grade ML solutions that drive smarter decisions, faster processes, and better outcomes for customers and colleagues. This isn't a prototyping role - you'll own problems from stakeholder consultation through to deployed, measurable solutions. Working in an agile pod, you'll also step into hands-on technical leadership and help shape ways of working through the Data Science Chapter community.

What you'll do

 * Develop, test, deploy and maintain end-to-end data science and analytics solutions
 * Build automation and ML-powered insight tools that improve business decision-making
 * Consult with stakeholders to translate complex business problems into analytics solutions
 * Provide technical leadership within your pod, setting engineering standards and direction


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