Data Scientist

What you'll work on

• Partner with business stakeholders to identify and prioritise opportunities where data science can deliver measurable value.
• Collect, clean, and transform structured and unstructured data from multiple internal and external sources.
• Develop, test, and deploy predictive models and machine learning algorithms to address business challenges.
• Conduct exploratory data analysis (EDA) to uncover trends, patterns, anomalies, and key drivers.
• Communicate insights and recommendations through clear storytelling, visualisations, and dashboards.
• Collaborate with engineering teams to productionise models and ensure reliability, scalability, and ongoing performance.
• Evaluate model accuracy and effectiveness, implementing continuous optimisation and tuning.
• Stay up to date with emerging data science tools, methodologies, and industry best practices.

Perform sensitivity analysis to assess model robustness and variable impact

What we're looking for

• At least 5 years’ experience in client‑facing data science roles with demonstrable impact on business outcomes.
• Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, Mathematics, or a related discipline.
• Strong proficiency in Python or R, including libraries such as pandas, scikit‑learn, NumPy, TensorFlow, or PyTorch.
• Solid understanding of statistical analysis, hypothesis testing, and experimental design.
• Hands‑on experience applying a range of supervised and unsupervised machine learning techniques (e.g., Random Forest, regression models, clustering methods).
• Proficiency with SQL and data warehousing technologies.
• Ability to translate complex analytical findings into clear, practical business recommendations.
• Strong problem‑solving skills and natural curiosity for exploring and understanding data.

• Experience working with cloud platforms such as Azure, AWS, or Google Cloud.
• Background in deploying machine learning models into production environments (MLOps experience is advantageous).
• Hands‑on experience with big‑data or distributed computing tools such as Spark or Databricks.
• Familiarity with visualisation tools such as Power BI, Tableau, or Plotly.
• Industry experience in sectors such as retail, finance, healthcare, or similar (customisable).

Key Competencies

• Strong analytical and conceptual thinking.
• Excellent communication and data‑storytelling capabilities.
• Effective collaboration and stakeholder‑engagement skills.
• High attention to detail and commitment to data accuracy.