Data Scientist

Overview

In this Data Scientist role, you partner with business stakeholders to identify high-impact opportunities where data science can drive measurable value. You will collect and prepare data from multiple sources, build and deploy predictive models, and translate insights into practical recommendations. You’ll work closely with engineering to productionize models and ensure reliability at scale, while staying updated on new tools and best practices. This position offers a chance to influence business outcomes across diverse industries within a global consulting environment.

Pay / Benefits

• flexible work options
• learning and development opportunities
• commitment to diversity and inclusion
• equal opportunities employer
• Disability Confident Committed Employer
• support for wellbeing and financial security

Responsibilities

• Partner with stakeholders to identify and prioritise data-driven opportunities
• Collect, clean, and transform structured and unstructured data from multiple sources
• Develop, test, and deploy predictive models and ML algorithms
• Conduct exploratory data analysis to uncover trends and drivers
• Communicate insights with storytelling, visualisations, and dashboards
• Collaborate with engineering to productionise models and ensure scalability and performance
• Evaluate model accuracy and perform continuous optimisation and tuning
• Stay up to date with emerging data science tools and methodologies
• Perform sensitivity analysis to assess model robustness and variable impact

Key requirements

• 5+ years in client-facing data science roles with demonstrable business impact
• Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, Mathematics, or related discipline
• Strong proficiency in Python or R with libraries like pandas, scikit-learn, NumPy, TensorFlow, or PyTorch
• Solid understanding of statistical analysis, hypothesis testing, and experimental design
• Hands-on experience with supervised and unsupervised ML techniques (e.g., Random Forest, regression, clustering)
• Proficiency with SQL and data warehousing technologies
• Ability to translate complex analytics into clear business recommendations
• Strong problem-solving skills and curiosity for data exploration

• Excellent communication and data storytelling
• Effective collaboration and stakeholder engagement
• High attention to detail
• Python or R with ML libraries (pandas, scikit-learn, NumPy, TensorFlow/PyTorch)
• Statistical analysis and experimental design
• SQL and data warehousing

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