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