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