Data Analyst job at Yalelo

Role Summary and Purpose

As a Data Analyst supporting the Production, Processing and Cooperate Services Departments in YU, you will be responsible for extracting valuable insights from data to optimize Production, Processing and Cooperate Services Operations.

Key Result Areas

SSOT, Data Analysis and Reporting:

• Collect, clean, and analyze Lake Ops, Processing, Cooperate Services & PSFU Data.
• Develop and maintain databases, ensuring data accuracy and integrity.
• Perform statistical analysis to identify trends, patterns, and anomalies.

Operational Improvement Strategy Support:

• Work closely with the Lake Ops, Processing, Cooperate Services & PSFU teams to ensure Operational Optimization and Process Improvement.
• Provide data-driven insights to support Process refinement, Optimization and Collaborate in the development of Data Driven insights in respective Departments.

Business Partnership Support

• Communicate complex data findings in a clear and understandable manner to Allocated Business Partners.
• Provide Data literacy Sessions to Business Partners where Applicable.
• Provide Data and Analytics Support where Applicable.
• Ensure Business Partner Data and Insights generated are Accurate and of High integrity.
• Provide Data Literacy Training to all respective Business Partnerships
• All Business Partner Insights Reporting is provided in a timely manner.

Performance Monitoring and Reporting

• Generate regular reports and dashboards to communicate key performance metrics to stakeholders.
• Identify and report on critical success factors and areas for improvement.
• Automate reporting processes to ensure timely delivery of insights.

Team Knowledge Exchange

• D&A Clerk dotted line reporting (Lake Ops Data Clerk) and Upskilling.
• Upskill of respective D&A Clerk as requested.
• Process documentation on D&A process flows and Bi reports.
• Perform other duties as assigned by your supervisor

Key Qualifications and Work Experience required for the role:

• Bachelor’s degree in Statistics, Computer Science.
• At least 3+ years of relevant experience as a Data Analyst/Scientist/Engineer.

Skills and Ability needed for the role:

• Database management systems and the ETL (Extract, Transform, Load) framework.
• Comprehensive knowledge of Excel, SQL, PowerBI, D365 and Python is desirable.
• Understanding of business processes, best practices, data lifecycles, and standard operating procedures.

Working conditions:

40 hours of work a week, with provisional extension of 8 hours as and when may be required.

• Collect, clean, and analyze Lake Ops, Processing, Cooperate Services & PSFU Data.
• Develop and maintain databases, ensuring data accuracy and integrity.
• Perform statistical analysis to identify trends, patterns, and anomalies.
• Work closely with the Lake Ops, Processing, Cooperate Services & PSFU teams to ensure Operational Optimization and Process Improvement.
• Provide data-driven insights to support Process refinement, Optimization and Collaborate in the development of Data Driven insights in respective Departments.
• Communicate complex data findings in a clear and understandable manner to Allocated Business Partners.
• Provide Data literacy Sessions to Business Partners where Applicable.
• Provide Data and Analytics Support where Applicable.
• Ensure Business Partner Data and Insights generated are Accurate and of High integrity.
• Provide Data Literacy Training to all respective Business Partnerships
• All Business Partner Insights Reporting is provided in a timely manner.
• Generate regular reports and dashboards to communicate key performance metrics to stakeholders.
• Identify and report on critical success factors and areas for improvement.
• Automate reporting processes to ensure timely delivery of insights.
• D&A Clerk dotted line reporting (Lake Ops Data Clerk) and Upskilling.
• Upskill of respective D&A Clerk as requested.
• Process documentation on D&A process flows and Bi reports.
• Perform other duties as assigned by your supervisor

• Database management systems and the ETL (Extract, Transform, Load) framework.
• Comprehensive knowledge of Excel, SQL, PowerBI, D365 and Python is desirable.
• Understanding of business processes, best practices, data lifecycles, and standard operating procedures.

• Bachelor’s degree in Statistics, Computer Science.