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.