Data Visualisation

1. Assists in the data collection and processing tasks 2. Integrates data from multiple sources and perform analysis to support business decisions 3. Identify new AI use cases and standard methodologies 4. Collaborate closely with functional area end-users to define requirements, diagnose, design and analyse information related to creation and adoption of solutions 5. Leverage on metrics and performance data to understand improvement opportunities 6. Deploy visualisation and generate reports that deliver insights to decision-makers 7. Provide expert functional and process mentorship on system capabilities

1. collect and analyse data from various sources to extract meaningful insights and inform business decisions. 2. design and create visualisations and dashboards to present data trends and findings to stakeholders. 3. clean, preprocess, and organise data to ensure accuracy and readiness for analysis. 4. perform statistical analysis using tools like Excel and Python to uncover patterns, correlations, and trends in data sets. 5. collaborate with cross-functional teams to understand data requirements and deliver actionable insights. 6. automate data collection and analysis processes to streamline operations and improve efficiency. 7. conduct data quality assessments and implement data cleansing techniques to maintain data integrity. 8. utilise machine learning and predictive modeling techniques to forecast trends and outcomes. 9. stay updated on data analysis techniques and tools to enhance analytical capabilities. 10. communicate findings and recommendations to non-technical stakeholders in a clear and understandable manner.

1. analyse large datasets using statistical methods and machine learning techniques to extract actionable insights. 2. develop predictive models and algorithms to forecast trends, behavior patterns, and business outcomes. 3. create visualisations and reports to communicate findings and recommendations to stakeholders. 4. implement machine learning models and algorithms for tasks such as image recognition, natural language processing, or recommendation systems. 5. collaborate with cross-functional teams to identify opportunities for data-driven solutions and business improvements. 6. clean and preprocess data to prepare it for analysis and modeling. conduct exploratory data analysis to understand patterns, trends, and anomalies in data. 7. evaluate and select appropriate machine learning models and techniques for specific problems. 8. deploy and maintain machine learning models in production environments. 9. stay updated on advancements in machine learning, artificial intelligence, and data science methodologies.

1. Analyse energy markets to understand supply and demand dynamics, price trends, and the impact of regulatory changes 2. Develop policies that promote efficient energy use, sustainability, and economic growth 3. Perform cost-benefit analyses for energy projects to make informed investment decisions 4. Forecast upcoming energy needs and pricing for planning and ensuring energy supply reliability 5. Identify ways to improve operational efficiency and reduce costs through data analysis 6. Assess the economic implications of environmental regulations and help design strategies to minimise negative impacts

1. Ensuring accurate data entry, system updates, and user support. 2. Analyse HR data and generate reports to support HR decision-making and strategic planning initiatives. 3. Provide training to HR staff and end-users on Human Resource Information Systems (HRIS) functionality and best practices for data management. 4. Collaborate with IT teams to integrate HRIS with other organisational systems and ensure data integrity and security. 5. Collect, analyse, and interpret HR data to identify trends, patterns, and insights that inform strategic decision-making. 6. Develop and generate regular and ad-hoc reports and dashboards to support HR initiatives and business operations. 7. Create visualisations (charts, graphs, etc.) to effectively communicate hr metrics and trends to stakeholders. 8. Ensure data accuracy, integrity, and compliance with data privacy regulations through regular audits and quality checks. 9. Monitor system performance and troubleshoot issues, providing timely resolutions to minimise disruptions. 10. Participate in the selection and implementation of new hris software and upgrades, ensuring alignment with organisational needs and goals.

1. Design and implement comprehensive performance evaluation processes to assess employee and system performance, providing actionable feedback aligned with organizational objectives. 2. Facilitate goal-setting processes to align individual, team, and system goals with overall business strategies, ensuring clarity and consistency across departments. 3. Analyze performance data to identify trends, strengths, and areas for improvement across teams and departments, driving continuous improvement and informed decision-making. 4. Develop, implement, and monitor performance improvement plans (PIPs) to address underperformance issues and support employee and system development. 5. Conduct training sessions and workshops for managers and employees on performance management best practices, ensuring effective evaluation and feedback mechanisms. 6. Lead or participate in cross-functional teams to implement process or system improvements, utilizing agile methods to enhance performance and optimize system solutions. 7. Collaborate with HR and management teams to ensure consistency, fairness, and alignment with industry standards in performance evaluations and processes. 8. Implement and manage performance recognition and reward programs to incentivize high performance, fostering a culture of excellence and achievement. 9. Ensure robust risk management by overseeing the management of change (MOC) processes and monitoring performance targets, contributing to organizational capability and compliance with health, safety, and security standards. 10. Coordinate knowledge-sharing sessions and mentoring programs, leveraging successful performance strategies and best practices both within and outside the organization to drive continuous improvement.