Data Science Lead

Job title:Data Science Lead

Purpose of the role:

• As a Data Scientist Lead, you will drive the design, deployment and continuous improvement of advanced ML and AI solutions – including Gen AI and LLMs to support analytical and insights activities including prediction, causal inference, anomaly detection, insights generation, etc utilised for decision making. You will ensure these solutions are robust, scalable, responsible and deliver measurable business value, with strong focus on data quality, MLOps and ethical AI practices.
• The ideal candidate will have a blend of advanced statistical experience and business acumen to support how we use data to transform optimisation and predictive insights for performance decisions. 
• The role sits within the Business Intelligence team supporting Enterprise Performance Management where our mission is empowering cross-functional partners with data and data-driven evidence to inform decisions. This will require close collaboration with BI Leads, Data Engineers and GB/GI stakeholders to optimise how we use and consume data to support strategic and operational objectives in the bank.

In this role, you will:

• Lead the end-to-end development and deployment of ML/AI solutions, including gen AI / LLMs, for performance decision-making e.g. financial forecasting, causal inference analysis, anomaly detection, insights generation, etc.
• Develop proof of concepts (PoCs) to validate research outcomes and demonstrate feasibility in operationalising into BAU framework, leveraging streamlined data technologies where appropriate.
• Navigate significant data complexity and technical debt involving financial and non-financial MI to provide high quality statistical solutions that accurately reflect business value-streams and multi-market landscape.
• Drive data quality assessments, data engineering and dataOps practices to ensure data is fit for ML/AI use across diverse markets and business services.
• Champion MLOps best practices for model versioning, monitoring and analysing system performance, identifying areas for improvement and implementing necessary changes to optimise model performance.
• Effectively prioritise and project manage the lifecycle of key projects from initial discovery through to production and stakeholder adoption
• Communicate complex technical concepts and model outcomes to both technical and non-technical audiences, enabling data-driven decision-making.
• Work within agile frameworks and participate in sprint planning to ensure timely and efficient delivery
• Collaborate with cross-functional teams – including BI Leads, Data Engineering, GB/GI stakeholders and AI experts to ensure solutions are user-centric and aligned with strategic priorities.
• Stay abreast of emerging trends in AI/ML, proactively identifying opportunities to apply new technologies for business impact.

To be successful you will:

Qualification:

• Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, or a related quantitative field.
• 5+ years’ experience developing, deploying, and maintaining ML/AI models in a business environment, with hands-on exposure to generative AI and LLMs.

Preferred Qualification:

• Experience in financial services, consulting, or large-scale operational environments.
• Certifications in cloud platforms (AWS, GCP, Azure) and MLOps technologies.

Key Competencies

• Highly proficient in Python or R and SQL, with experience leveraging cloud-based platforms (e.g. GCP) to scale statistical applications.
• Strong experience with machine learning frameworks (e.g. TensorFlow, PyTorch), LLM APIs (e.g. OpenAI), and data engineering tools.
• Strong grasp of advanced statistical modelling and causal inference methods with proven track record in building forecasting or econometric models
• Demonstrated expertise in MLOps, model monitoring, and responsible AI practices.
• Deep understanding of data quality, cleansing, and enhancement techniques.
• Excellent communication, stakeholder management, and project leadership skills.
• Ability to work collaboratively across teams and geographies, valuing diverse perspectives and fostering an inclusive environment.
• Strong business acumen and a product mindset, with a track record of delivering measurable business impact.
• Experience managing large projects independently with proven ability to define and improve roadmap to successful delivery

What additional skills will be good to have?

• Experience with business intelligence and visualisation tools (Power BI, Tableau, QlikSense).
• Knowledge of regulatory and compliance considerations in data science.
• Passion for continuous learning and staying ahead of AI/ML trends.

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You’ll achieve more at HSBC

HSBC is an equal opportunity employer committed to building a culture where all employees are valued, respected and opinions count. We take pride in providing a workplace that fosters continuous professional development, flexible working and, opportunities to grow within an inclusive and diverse environment. We encourage applications from all suitably qualified persons irrespective of, but not limited to, their gender or genetic information, sexual orientation, ethnicity, religion, social status, medical care leave requirements, political affiliation, people with disabilities, color, national origin, veteran status, etc., We consider all applications based on merit and suitability to the role.”

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