Senior Data Scientist (ML)
London, GB, E14 5NR
Job description
If you’re looking for a career that will help you stand out, join HSBC, and fulfil your potential - whether you want a career that could take you to the top, or an exciting new direction, we offer opportunities, support and rewards that will take you further.
We’re one of the largest banking and financial services organisations in the world, with a network that covers more than 50 countries and territories. We aim to be where the growth is, enabling businesses to thrive and economies to prosper, and, ultimately, helping people fulfil their hopes and realise their ambitions.
We’re currently seeking an experienced professional to join our team in the role of Senior Data Scientist (ML).
This role combines strong engineering with hands-on applied machine learning across ML and GenAI services used in Wholesale banking. You’ll help turn PoC and PoV work into reliable production solutions with clear non-functional requirements and defined service ownership. The work supports AI applications that identify new business opportunities flag risks of client attrition and strengthen how we serve customers. Success means robust evaluation and monitoring across messy and imbalanced datasets repeatable releases through strong MLOps and LLMOps and solutions that stand up to control and audit expectations.
As an HSBC employee in the UK, you’ll have access to tailored professional development opportunities and a competitive pay and benefits package. This includes private healthcare for all UK-based employees, enhanced maternity and adoption pay and support when you return to work, and a contributory pension scheme with a generous employer contribution.
In this role you will:
- Design build deploy and operate production-grade AI services (ML and or GenAI) that are secure scalable and reusable
- Productionise PoC and PoV work into hardened solutions with clear performance resilience cost and security requirements and defined service ownership
- Build and maintain MLOps and LLMOps pipelines including CI/CD automated testing packaging promotion and rollback and model and version management
- Develop and implement model evaluation approaches for complex and imbalanced datasets including defining metrics validation methods and performance trade-offs
- Implement observability for AI services including logging metrics tracing model performance monitoring and quality and drift checks with actionable alerting
- Build inference pipelines using the Python ML ecosystem and ML or DL frameworks such as PyTorch or TensorFlow
- Partner with data scientists and data engineers to integrate data pipelines feature inputs and evaluation results into production services
- Translate business requirements into technical and modelling designs and communicate trade-offs and recommendations clearly to technical and non-technical stakeholders
To be successful in this role you should meet the following requirements:
- Bring strong software engineering experience delivering end-to-end services in production with ownership for run and support considerations
- Demonstrate proficiency in Python and modern engineering practices including clean code testing packaging dependency management and Git-based workflows
- Apply hands-on experience with AI deployment patterns and infrastructure such as Docker Kubernetes API-based serving and batch or stream inference
- Use practical MLOps experience including CI/CD for ML model packaging release management automated validation monitoring and lifecycle management
- Work with ML and DL frameworks and tooling such as PyTorch or TensorFlow and the Python ML ecosystem to implement training adjacent evaluation and inference pipelines
- Evaluate model performance on large messy and imbalanced datasets and explain trade-offs in metrics and approach to stakeholders
- Build and deploy web APIs using libraries such as Flask or FastAPI
- Use database technologies such as SQL Server or Postgres
- Explain technical designs risks and operational considerations clearly to wide-ranging audiences
- Manage delivery across multiple initiatives through prioritisation and time management
Opening up a world of opportunity.
Being open to different points of view is important for our business and the communities we serve. At HSBC, we’re dedicated to creating diverse and inclusive workplaces - no matter their gender, ethnicity, disability, religion, sexual orientation, socio-economic background or age. We are committed to removing barriers and ensuring careers at HSBC are inclusive and accessible for everyone to be at their best. We take pride in being a Disability Confident Leader and will offer an interview to people with disabilities, long term conditions or neurodivergent candidates who meet the minimum criteria for the role.
If you have a need that requires accommodations or changes during the recruitment process, please get in touch with our Recruitment Helpdesk via hsbc.recruitment@hsbc.com.