Senior Data Scientist MMH

To apply advanced analytics, statistical modelling, machine learning and investment-domain insight to solve complex business problems, improve investment and client outcomes, and accelerate the organisation’s digital transformation. The role converts data into scalable intelligence, decision-support tools and digital solutions that enable investment professionals, distribution teams, operations and clients to make faster, better-informed decisions.

• Bachelor’s degree in data science, Statistics, Mathematics, Computer Science, Engineering, Econometrics, Quantitative Finance or a related quantitative discipline.
• A postgraduate qualification in a relevant discipline is advantageous.
• 5 to 7 years’ relevant experience in data science, advanced analytics or machine learning; the required depth may vary with role level.
• Demonstrated experience delivering analytical models or data products beyond proof-of-concept stage.
• Experience in investments, asset management, wealth management, financial services or another regulated environment is strongly preferred.
• Experience working in agile, multidisciplinary digital or product teams would be an advantage.

• Frame ambiguous business challenges as clear analytical questions, hypotheses and measurable outcomes.
• Explore, clean, combine and analyse structured and unstructured data from internal and external sources.
• Develop, validate and maintain statistical, machine-learning and optimisation models.
• Apply techniques such as segmentation, propensity modelling, forecasting, anomaly detection, natural language processing and recommendation methods where appropriate.
• Design robust experiments and evaluate the causal and commercial impact of digital interventions.
• Translate complex analysis into clear recommendations, visual narratives and decision-ready insights.

• Partner with investment professionals to identify opportunities where data can strengthen research, portfolio insight, risk awareness and decision support.
• Analyse client, adviser, product, market and transactional data to identify behavioural patterns, needs and emerging opportunities.
• Support the development of personalised propositions, next-best-action capabilities and digitally enabled investment experiences.
• Contribute analytical insight to product development, distribution effectiveness, client retention and operational optimisation.
• Ensure that model outputs are interpreted within the relevant investment, market and client context.

• Work in cross-functional product teams with data engineers, software engineers, designers, product owners, architects and business specialists.
• Convert prototypes into maintainable, monitored and reusable analytical services or data products.
• Define model features, interfaces, acceptance criteria and monitoring requirements for deployment.
• Apply sound software-engineering practices, including version control, testing, documentation and peer review.
• Monitor model performance, drift, data quality and business impact, and initiate enhancements where required.
• Contribute to reusable analytical assets, standards and communities of practice.
• Design, develop and ope rationalise Agentic AI solutions and agentic workflows that can reason, plan and execute defined tasks, incorporating appropriate human oversight, testing, monitoring, security and governance controls.

• Comply with data privacy, information security, model governance, regulatory and records-management requirements.
• Document data lineage, assumptions, limitations, validation results and intended use of analytical models.
• Assess models for bias, fairness,…