Data Scientist

RESPONSIBILITIES & TASKS

Data Exploration and Analysis

• Perform exploratory data analysis on enterprise datasets to identify trends, patterns, anomalies, and opportunities.
• Develop analytical frameworks to support operational, commercial, and strategic decision-making.
• Translate business problems into analytical questions, hypotheses, and measurable outcomes.

Predictive and Prescriptive Analytics

• Develop predictive, classification, forecasting, segmentation, recommendation, and optimization models.
• Build statistical models to support business planning, resource allocation, and performance improvement.
• Conduct scenario modelling, sensitivity analysis, and what-if analysis to guide management decisions.
• Evaluate model effectiveness, explain results, and assess business impact.

AI and Machine Learning

• Collaborate with AI/ML Engineers to operationalize models into reliable production solutions.
• Support experimentation with Generative AI, Agentic AI, and advanced analytics use cases.

Business Intelligence and Executive Insights

• Prepare executive-level insights, recommendations, dashboards, and presentations.
• Develop reports and visualizations that clearly communicate business performance and analytical findings.
• Support KPI definition, measurement frameworks, and value realization tracking for AI and analytics initiatives.

Data Governance and Quality

• Promote high-quality, trusted, and responsible data usage across analytics and AI activities.
• Support the establishment of data standards, data definitions, and governance practices.
• Monitor data quality and ensure analytical outputs are based on fit-for-purpose data.
• Ensure compliance with privacy, regulatory, and information security requirements.

Research and Innovation

• Evaluate emerging analytics and AI technologies, modelling techniques, and business applications.
• Identify new opportunities to create competitive advantage using data, analytics, and AI.

SKILLS & QUALIFICATIONS

• Minimum 6 years of experience in Data Science, Advanced Analytics, Business Analytics, Statistics, or related disciplines.
• Bachelor’s degree in Data Science, Statistics, Mathematics, Computer Science, Engineering, Economics, or a related discipline.
• Experience delivering business insights through data analysis, developing predictive and machine learning models, and engaging directly with business stakeholders.

Technical Skills

• Python
• R desirable
• SQL
• Machine learning
• Statistics and experimental design
• Forecasting techniques
• Data visualization and storytelling
• Power BI or equivalent BI tools
• Snowflake or modern cloud data platforms
• Data modelling and feature engineering