Data Analyst

at  Applegreen Stores

EDUCATION, QUALIFICATIONS & EXPERIENCE:

• Bachelor’s degree in a relevant field such as Statistics, Mathematics, Computer Science, or a related discipline. Advanced degrees (Master’s or Ph.D.) may be preferred.
• Proficiency in programming languages such as SQL, Python, or R.
• Experience with data visualization tools like Tableau, Power BI, or similar.

KEY SKILLS & ATTRIBUTES:

• Strong analytical and problem-solving skills.
• Excellent communication skills to convey complex findings in a clear and understandable manner.
• Knowledge of database systems, data warehousing, and data modelling concepts.

• Data Collection and Processing:
• Collect, clean, and preprocess data from various sources to ensure accuracy and completeness.
• Develop and implement data collection systems and other strategies to optimize statistical efficiency and data quality.
• Data Analysis:
• Perform exploratory data analysis (EDA) to identify patterns, trends, and outliers.
• Use statistical techniques to analyse data and extract meaningful insights.
• Develop and implement data models, algorithms, and simulations.
• Performance Analysis:
• Analyse charging station performance metrics to ensure optimal functionality and identify opportunities for improvement.
• Assess reliability, downtime, and efficiency of charge points.
• Fault Detection and Resolution:
• Implement algorithms and monitoring systems to detect faults and anomalies in real-time.
• Collaborate with maintenance teams to quickly resolve issues and minimize downtime.
• Energy Efficiency and Optimisation:
• Identify opportunities for improving energy efficiency through data analysis.
• Collaborate with engineers and other teams to implement and monitor efficiency initiatives.
• Data Visualisation:
• Create clear and compelling visualisations (charts, graphs, dashboards) to communicate findings to non-technical stakeholders.
• Use tools such as Tableau, Power BI, or other visualisation tools to present data in an understandable and actionable format.
• Reporting:
• Generate regular and ad-hoc reports to provide insights and support decision-making processes.
• Collaborate with cross-functional teams to understand reporting requirements and deliver actionable insights.
• Collaboration:
• Collaborate with other departments, data scientists, and business stakeholders to understand data needs and provide analytical support.
• Work closely with IT teams to ensure data accuracy, availability, and security.