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.