The Role Purpose:  We are seeking a Data Scientist to join our team, with a primary focus on analysing complex datasets, developing predictive and statistical models, and generating actionable insights that enable smarter business decisions.  The successful candidate will combine strong analytical and problem-solving capabilities with practical experience in machine learning, statistical modelling, and data-driven decision-making. This role focuses on leveraging data to solve business challenges through forecasting, predictive analytics, and advanced modelling techniques.  The successful candidate will play a key role in helping the organisation unlock value from its data and build scalable analytical solutions that drive business outcomes.  Your Responsibilities will include:  * Analyse large and complex datasets to identify trends, patterns, and opportunities for business improvement.  * Develop, test, and deploy predictive and statistical models to solve business problems.  * Build and maintain data models that support business intelligence and decision-making initiatives.  * Design and implement machine learning solutions for use cases such as customer churn prediction, fraud detection, forecasting, and customer segmentation.  * Prepare, clean, and transform structured and unstructured data for analysis and modelling.  * Conduct exploratory data analysis and communicate findings and recommendations to stakeholders.  * Develop and maintain reporting, dashboards, and analytical solutions that provide actionable insights.  * Monitor, evaluate, and improve the performance and accuracy of predictive models.  * Collaborate with business stakeholders to understand requirements and translate them into data-driven solutions.  * Work closely with Data Engineers and technology teams to ensure data quality, accessibility, and governance.  * Document methodologies, assumptions, and analytical processes to ensure repeatability and knowledge sharing.  * Stay informed of emerging technologies and best practices within Data Science and analytics.  The ideal candidate for the role will have the following qualifications, experience and knowledge:  Educational Background:  * Bachelor's Degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, Information Technology, or a related quantitative field.  * Postgraduate qualification in Data Science, Applied Mathematics, Statistics, Machine Learning, or Artificial Intelligence is advantageous.  * Relevant certifications in Data Science, Machine Learning, or cloud platforms are advantageous.  Work Experience:  * 3–5 years of experience as a Data Scientist delivering analytical and predictive solutions in production environments.  * Proven experience developing and deploying machine learning and statistical models to solve business problems.  * Experience working with large datasets and building data-driven solutions that deliver measurable business value.  * Experience collaborating with cross-functional teams and translating business requirements into analytical solutions.  * Exposure to cloud-based data platforms and modern data ecosystems is advantageous.  Knowledge:  * Strong understanding of machine learning algorithms, statistical modelling techniques, and predictive analytics.  * Knowledge of data preparation, feature engineering, and model evaluation methodologies.  * Understanding of data modelling principles and analytical frameworks.  * Familiarity with data governance, data quality, and best practices for handling enterprise data.  * Exposure to Generative AI technologies and Retrieval-Augmented Generation (RAG) concepts is advantageous but not required.  Technical Skills:  Data Science & Analytics  * Python for data analysis and machine learning.  * SQL and relational databases.  * Statistical modelling and predictive analytics.  * Data wrangling, cleansing, and feature engineering.  * Data visualisation and reporting.  Machine Learning  * Supervised and unsupervised learning techniques.  * Model evaluation and performance optimisation.  * Forecasting and predictive modelling.  * Classification and regression techniques.  Data Platforms & Tools  * Experience with cloud data platforms such as Azure, AWS, or GCP is advantageous.  * Experience with data warehouses such as Snowflake, BigQuery, or similar platforms is advantageous.  * Familiarity with notebooks and analytical tools such as Jupyter.  AI & Emerging Technologies (Advantageous)  * Exposure to Large Language Models (LLMs) and Generative AI concepts.  * Familiarity with Retrieval-Augmented Generation (RAG) principles.  * Exposure to frameworks such as LangChain is advantageous but not required.  Engineering & Delivery  * Strong problem-solving and analytical thinking capabilities.  * Ability to communicate technical concepts and insights to both technical and non-technical stakeholders.  * Experience working in Agile delivery environments.  * Strong documentation and presentation skills.