Associate Data​/Decision Scientist

Key Accountabilities

• Perform data preparation, cleaning, and analysis
• Support the development of analytical models and data pipelines across key use cases
• Assist in implementing machine learning, statistical, and optimization models under guidance from senior team members
• Perform data cleaning, preprocessing, and exploratory data analysis (EDA)
• Translate analytical outputs into clear insights, visualizations, and reports
• Support the delivery of data-driven recommendations to inform operational and strategic decisions
• Contribute to dashboards and tools that enhance visibility into performance and forecasts
• Develop dashboards and reports on the CoE's BI platforms
• Support AI model development, testing, and documentation
• Work closely with the Senior Decision Scientist to build and refine models
• Validate results and ensure quality outputs and understand business context and decision frameworks
• Participate in code reviews, model reviews, and knowledge-sharing sessions
• Ensure high standards of data integrity, quality checks, and documentation
• Work with structured and unstructured datasets from multiple sources
• Support the maintenance of reproducible and well-documented codebases
• Build foundational skills in data science, AI, and platform tools through structured development
• Apply best practices in coding, modeling, and analytics inspired by industry-leading organizations
• Engage with stakeholders across operations, digital, and strategy teams to understand data needs
• Support the translation of business questions into analytical tasks
• Communicate findings in a clear and structured manner appropriate for different audiences

• Bachelor's degree in Computer Science, Data Science, Engineering, or a related field; UAE National (National Talent programme).
• Strong foundation in statistics, linear algebra, and data analysis.

• 1-3 years of experience in data science, analytics, or related fields (internships included).
• Job-Exposure to energy, utilities, or financial analytics is advantageous but not mandatory.
• Demonstrated experience working on data-driven projects (academic or professional).

• Proficiency in Python, SQL, or similar programming languages.
• Familiarity with data analysis libraries (e.g., Pandas, Num Py).
• Visualization tools (e.g., Power BI, Tableau, Matplotlib).
• Basic machine learning concepts and frameworks.
• Understanding of data pipelines and data wrangling techniques.
• Exposure to cloud platforms or big-data tools is a plus.

• Strong analytical thinking and problem-solving skills.
• Curiosity and eagerness to learn and grow in a fast-paced environment.
• Ability to take direction, absorb feedback, and continuously improve.
• Good communication skills with the ability to explain findings clearly.
• Collaborative mindset and strong attention to detail.