1. Data Analysis and Interpretation:

• Collect, process, and analyze large datasets from multiple sources, including financial, operational, and market data.
• Identify patterns, trends, and correlations within the data that can provide actionable insights for decision-making.
• Translate complex data analyses into clear, understandable reports and presentations for both technical and non-technical stakeholders.

1. Data-Driven Decision Support:

• Collaborate with the portfolio management, finance, and operations teams to integrate data analytics into business planning and decision-making processes.
• Provide recommendations on optimizing asset performance, reducing costs, and maximizing returns based on data-driven insights.
• Support scenario analysis and stress testing to assess the impact of different strategies and market conditions.

1. Data Visualization and Reporting:

• Create interactive dashboards and visualizations that allow stakeholders to explore and understand key metrics and trends.
• Ensure that data visualizations are tailored to the needs of different audiences, from senior management to operational teams.
• Maintain and update reporting tools to provide real-time insights into portfolio performance and other key metrics.

1. Data Governance and Quality Assurance:

• Establish and maintain data governance practices to ensure the accuracy, consistency, and security of data.
• Work with IT and other departments to ensure data is collected, stored, and processed in compliance with company policies and regulations.
• Conduct regular audits and validations to maintain the integrity of datasets and models

• ​​​  5. Innovation and Continuous Improvement:Stay up to date with the latest developments in data science, analytics, and machine learning to continuously improve methodologies and tools.
• Propose and implement innovative solutions that leverage data to address complex business challenges.
• Foster a data-driven culture within the organization by promoting the value of analytics and encouraging the use of data in decision-making

Skills

• Education: Bachelor’s degree in Data Science, Computer Science, Statistics, Mathematics, or a related field.
• A master’s degree or Ph.D. in a relevant discipline is preferred.
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• Experience: At least 5-8 years of experience in data science, analytics, or a related field, with a strong focus
• on data-driven decision support. Experience in the infrastructure or asset management industry is a plus.
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• Skills:
• Proficiency in programming languages such as Python, R, or SQL.
• Strong knowledge of machine learning algorithms, statistical analysis, and data mining techniques.
• Experience with data visualization tools such as Tableau, Power BI, or similar platforms.
• Ability to translate complex data into actionable insights and communicate them effectively to non-technical stakeholders.
• Experience in working with large datasets and databases, including cloud-based data storage solutions.
• Strong problem-solving skills and a proactive approach to identifying and addressing challenges.
• Ability to independently drive initiatives, from concept to implementation, within the data science domain.
• Excellent communication skills, with the ability to work collaboratively across departments and present data-driven insights to diverse teams.