and 3rd party panels to test fast-evolving hypotheses. Design and automate reporting processes , bringing visibility to crucial metrics and freeing teams to act on what matters most. Build statistical models and algorithms to detect patterns and opportunities for optimisation. Create compelling data visualisations using Grafana and Power BI to track performance in real time. Communicate complex analytical findings … across the business. YOUR SKILLS AND EXPERIENCE: The ideal Senior Data Analyst will have: Proficiency in Python or R , with hands-on experience building analytical models. Strong knowledge of statistical techniques , from regressions to machine learning algorithms. Excellent SQL and data manipulation skills , with experience working on large, complex datasets. Familiarity with cloud data platforms such as AWS, Azure More ❯
growing, with excellent visibility across the business and a genuine appetite for data innovation. Key Responsibilities Optimise existing yield and matching models for better consistency and forecasting performance. Use statistical analysis to uncover trends in historical trading data and recommend actionable improvements. Build and deploy scalable data science solutions that drive measurable business impact. Collaborate with developers and commercial … and experience working with SQL and data visualisation tools such as Power BI. Familiarity with cloud platforms such as AWS, Redshift, or Azure. Strong grasp of forecasting, optimisation, and statisticalmodelling techniques. Confident communicator who can translate technical outputs into business recomme ndations. Comfortable working in agile, iterative environments with cross-functional teams. **Please note: Unfortunately, this role More ❯
code and architectural reviews, as well as technical mentoring. Data Science Enablement Act as Data Scientist to support analytics and decision-making needs. Develop experimentation frameworks, metric definitions, and statistical models. Help define the future structure, tools, and hiring profile for the Data Science function. Required Qualifications: Proven experience building and deploying GenAI applications in production. Strong hands-on … knowledge of LLMs, prompt engineering, and retrieval-augmented generation (RAG). Practical experience with traditional ML, including data pipelines and MLOps workflows. Working knowledge of statisticalmodelling and experimentation. Proficiency in Python and at least one additional general-purpose language. Strong understanding of cloud-native architectures (AWS preferred). Experience leading technical teams and mentoring engineers. Excellent stakeholder More ❯
