Principal DevOps Architect III

Job ID
2026-8723
Category
Technical/Engineering
Job Location
UK-Remote

Position Overview

SBS is seeking a Lead/Principal Data Scientist to join its growing Data & AI function in the UK. This is a senior, high-impact role responsible for shaping and delivering advanced data science solutions across SBS products and client engagements.

 

The successful candidate will combine deep technical expertise with strategic leadership, driving the development of scalable AI/ML models, influencing product innovation, and enabling clients to unlock value from their data.

 

Location: Greater London, UK

Hybrid: Flexible Onsite Schedule

Responsibilities

Data Science Leadership

  • Lead the design and delivery of advanced analytics, machine learning, and AI solutions across SBS platforms and client projects
  • Act as a technical authority for data science, setting best practices and standards across the organization
  • Mentor and guide junior and senior data scientists, fostering a high-performance, collaborative team environment

Model Development & Deployment

  • Develop and deploy machine learning models for use cases such as:
  • Fraud detection
  • Credit risk modeling
  • Customer segmentation and personalization
  • Forecasting and optimization
  • Ensure models are scalable, explainable, and production-ready
  • Work closely with engineering teams to operationalize models within production environments (MLOps)

Product & Innovation

  • Partner with Product, Engineering, and Architecture teams to embed AI capabilities into SBS solutions
  • Identify opportunities to leverage AI/ML to enhance banking products and client outcomes
  • Drive innovation through experimentation with emerging technologies (e.g., GenAI, LLMs, predictive analytics)

Client Engagement & Stakeholder Management

  • Engage with clients and internal stakeholders to understand business challenges and translate them into data science solutions
  • Present insights, models, and recommendations to senior leadership and client executives
  • Act as a trusted advisor on data strategy and AI adoption

Data Strategy & Governance

  • Support the development of data strategy frameworks, ensuring alignment with regulatory and compliance requirements
  • Promote best practices in data governance, model validation, and ethical AI usage

Qualifications

Required Background:

  • MSc or Higher in Artificial Intelligence, Computer Science, Data Science, or a closely related discipline
  • Strong grounding in machine learning, Generative AI, Agentic AI, explainable AI (XAI), and type-2 fuzzy logic systems
  • Additional training or certification in cloud computing, software engineering best practices, or data security (desirable)

Required Skills:

  • Proficiency in Generative and Agentic AI
  • Proficiency in AI/ML model development, including feature selection, XAI techniques, and consensus modelling
  • Strong programming skills (e.g., Python, Java, or similar) and experience with open-source AI libraries
  • Ability to integrate AI models into commercial software architectures and ensure compliance with GDPR and security standards
  • Excellent analytical and problem-solving skills; capable of designing and validating algorithms
  • Strong communication skills, stakeholder engagement, and technical reporting
  • Experience with Generative AI Retrieval-Augmented Generation, and cloud deployment
  • Familiarity with financial data structures and API integration (desirable)

Required Attributes:

  • Highly motivated, adaptable, and able to work independently while collaborating with academic and industry teams
  • Commercial awareness and ability to align technical solutions with business objectives
  • Strong organizational skills to manage complex, multi-stage projects
  • Strong written and spoken English, with excellent communication skills

Preferred Experience:

  • Advanced degree (Master’s or PhD) in Data Science, Computer Science, Statistics, Mathematics, or related field
  • Experience with GenAI / LLMs and NLP applications
  • Knowledge of regulatory frameworks in financial services (e.g., GDPR, model risk governance)

 

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