Data Scientist

Overview

As a data scientist in this role, you partner with stakeholders to identify high-impact opportunities where data science drives measurable value. You will collect and shape data, build and deploy predictive models, and share clear insights to influence business decisions. You collaborate with engineering to productionise solutions, continuously optimize models, and stay at the forefront of data science practices. This position offers meaningful work at scale within a globally oriented, inclusive consulting environment.

Pay / Benefits

• flexible work options
• learning and development opportunities
• wellbeing support

Responsibilities

• Partner with business 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 through storytelling, visualisations, and dashboards
• Collaborate with engineering to productionise models and ensure reliability
• Evaluate model accuracy and implement continuous optimization
• Stay updated with emerging data science tools and best practices
• 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
• Proficiency in Python or R with libraries such as pandas, scikit-learn, NumPy, TensorFlow, or PyTorch
• Strong understanding of statistics, 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 analytical findings into practical business recommendations
• Strong problem-solving skills and natural curiosity

• Excellent communication and data storytelling
• Effective collaboration and stakeholder engagement
• High attention to detail and commitment to data accuracy
• Python or R with pandas, scikit-learn, NumPy; TensorFlow or PyTorch
• SQL and data warehousing
• Statistical analysis, hypothesis testing, experimental design

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