Data Scientist

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.