As a Data Scientist with a strong data analytics focus, you will sit at the intersection of data, technology, and business strategy. You will play a critical in transforming large, complex datasets into meaningful insights that directly influence operational, commercial, and strategic decision-making across the organization.
Key Responsibilities
- Lead the analysis of structured and unstructured datasets to uncover trends, patterns, risks, and opportunities that support data-driven business decisions.
- Develop, maintain, and optimize dashboards, reports, and visualizations using modern BI and analytics tools to communicate insights clearly to both technical and non-technical stakeholders.
- Design, build, test, and deploy predictive and machine learning models that improve forecasting accuracy, operational efficiency, customer experience, and business performance.
- Perform advanced statistical analysis and exploratory data analysis (EDA) to identify actionable recommendations and support strategic initiatives.
- Partner closely with business stakeholders, product teams, engineers, and leadership groups to translate business requirements into scalable analytical solutions.
- Own the full analytics and data science lifecycle, including data extraction, cleansing, transformation, feature engineering, validation, model evaluation, deployment, and ongoing performance monitoring.
- Develop automated reporting and analytics workflows to improve efficiency, reduce manual effort, and increase data accessibility across teams.
- Work with large-scale data environments and cloud-based platforms to ensure analytical solutions are scalable, secure, and production-ready.
- Present findings, trends, and recommendations through compelling storytelling, data visualization, and executive-ready insights.
- Continuously evaluate emerging technologies, statistical techniques, and AI/ML methodologies to drive innovation and improve analytical capabilities.
Technical & Analytical Focus
- Strong focus on data interpretation, trend analysis, and translating complex findings into practical business recommendations.
- Experience working with SQL, Python, R, or similar analytical programming languages for data manipulation, statistical analysis, and machine learning.
- Ability to work with large datasets across multiple systems and sources while maintaining high levels of data accuracy and integrity.
- Knowledge of predictive analytics, regression analysis, clustering, classification models, and forecasting techniques.
- Experience with data visualization and reporting tools such as Power BI, Tableau, Looker, or equivalent platforms.
- Understanding of KPI development, performance measurement frameworks, and operational/business analytics.
- Strong problem-solving mindset with the ability to identify root causes, quantify business impact, and recommend evidence-based solutions.
Collaboration & Business Impact
- Act as a trusted analytical partner to business stakeholders by delivering insights that influence strategic planning and operational priorities.
- Collaborate across technical and business functions to improve data literacy and promote a culture of evidence-based decision-making.
- Support senior leadership with ad hoc analysis, scenario modelling, forecasting, and business performance reporting.
- Contribute to long-term data strategy initiatives, helping shape how data is collected, governed, analyzed, and leveraged across the organization.
What Success Looks Like
- Delivering high-quality analytical outputs that drive measurable business outcomes.
- Building scalable, reliable reporting and analytical solutions that improve visibility and decision-making.
- Providing clear, concise, and commercially relevant recommendations backed by robust data analysis.
- Helping teams move from reactive reporting toward proactive, predictive, and insight-led decision-making.
**This role is ideal for an analytically minded professional who combines strong technical capability with commercial awareness and a passion for using data to solve complex business challenges.