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.