Data Scientist

Airswift; London; Hybrid; GBP 50,000 - 70,000; Full time

Job summary

A leading tech recruitment agency is looking for a Data Scientist to join a prestigious project in London. This contract role emphasizes collaboration with engineering teams and utilizes tools like Azure and GitLab. Applicants should possess strong statistical analysis, programming skills in Python and SQL, and experience in machine learning. The position offers a flexible hybrid working environment in Central London.

Qualifications

• Proven experience in developing and implementing AI solutions, including classification, clustering, and anomaly detection.
• Experience in coding for production-level data analysis.
• Background in data science or modeling roles within DevOps or cloud-focused projects.

Responsibilities

• Configure and optimize Nexus Lifecycle and CI/CD integration.
• Deploy and scale workloads using Azure Kubernetes Service.
• Manage Maven POM configurations for dependency management.

Skills

Statistical data analysis

Machine learning

Natural Language Processing (NLP)

Python programming

SQL

Cloud Computing

ML Ops

GitLab

JIRA

Education

Degree in Computer Science or Engineering

Tools

Azure Kubernetes Service

Azure AI Search

Job description

Data Scientist





Job Type: Contract


Work Period: Hybrid (3 days onsite per week)


Duration: Until December 2025 (Possibility of renewal)


Location: Central London, near Liverpool Street Station





Take the Lead in Data Science and CI/CD Integration


We are seeking a skilled and experienced Data Scientist / Data Modeler to support a client on a project. This hybrid contract position involves close collaboration with engineering teams and regular presence at the office in Central London.





Role Overview


As a Data Scientist, you will:

• Configure and optimize Nexus Lifecycle, including integration into CI/CD pipelines
• Manage Maven POM configurations, handling dependency management and plugin setup
• Deploy and scale workloads using Azure Kubernetes Service (AKS)
• Apply best practices in Kubernetes scaling and autoscaling in production environments
• Contribute to Azure migration efforts and cloud- architecture
• Develop and maintain automation scripts using Bash, Shell, or similar
• Configure and manage GitLab pipelines for CI/CD workflows
• Implement Git and CI configuration best practices
• Collaborate with engineering and DevOps teams to ensure secure, scalable deployment pipelines

• Your Expertise
• Proficient in statistical data analysis, machine learning, and NLP, with a clear understanding of practical applications and limitations
• Experienced in developing and implementing AI solutions, including classification, clustering, anomaly detection, and NLP
• Proficient in Python programming and SQL, with experience in production-level code and data analysis libraries
• Familiar with ML Ops, model development workflows, and feature engineering techniques
• Capable of manipulating data and developing models accessible for business use, with experience in Azure AI Search
• Adept with software development methodologies, code versioning (e.g. GitLab), and project tracking tools (e.g. JIRA)
• Additional knowledge in Cloud Computing, Big Data tools, visualization tools, and containerization tools is beneficial

• Education & Experience
• Qualifications: Degree in Computer Science, Engineering, or a related field
• Experience: Proven background in data science or modeling roles within DevOps or cloud-focused projects

• The Next Step
  
  
  If you bring solid experience in planning and risk and are ready to contribute to a world-class gas development project, we want to hear from you. Even if your background isn’t a perfect match, we welcome candidates with strong transferable skills.
  
  
  Apply now with your updated CV or contact Mylena Marques at [e-mail]
  
  
  #LI-MM14