Commercial Data Analyst

M-Gas Kenya is an energy company focused on providing clean cooking solutions. Founded in 2015, it operates in the Energy & Utilities sector.

The Commercial Data Analyst is responsible for delivering actionable commercial insights that support customer growth, retention, revenue optimization, and overall business performance. The role combines advanced business intelligence, data analysis, dashboard development, and reporting automation to enable data-driven decision-making across the Commercial function. Working closely with the Division Head – Commercial and the Growth & Retention teams, the incumbent will transform complex datasets into meaningful insights, develop and maintain interactive dashboards, and support the continuous improvement of reporting infrastructure through periodic backend BI development and coding.

1. Analyze commercial performance across customer acquisition, activation, retention, churn, revenue, and lifetime value.
2. Identify trends, patterns, risks, and growth opportunities using customer and commercial data.
3. Develop recurring and ad hoc analyses to support strategic and operational decision-making.
4. Monitor key commercial KPIs and provide timely performance insights.
5. Conduct cohort, funnel, segmentation, and customer behavior analyses.
6. Support pricing, campaign, and product performance evaluations through data-driven insights.
7. Design, develop, and maintain interactive dashboards and scorecards using BI tools such as Power BI, Tableau, or Looker.
8. Perform backend dashboard development, including data modelling, DAX calculations, SQL queries, and report optimization.
9. Troubleshoot and enhance existing dashboards to improve functionality, usability, and performance.
10. Develop automated reporting solutions that reduce manual effort and improve reporting accuracy.
11. Ensure dashboards provide consistent, accurate, and reliable commercial performance metrics.
12. Extract, clean, validate, and transform data from multiple sources.
13. Build and maintain datasets that support commercial reporting requirements.
14. Ensure data integrity through regular validation and reconciliation.
15. Develop standardized reporting templates for Commercial leadership.
16. Document reporting logic, data definitions, and dashboard specifications.
17. Partner with Growth, Retention, Marketing, Sales, Finance, Product, and Customer Experience teams to understand business requirements.
18. Translate business questions into analytical solutions.
19. Present findings and recommendations to senior leadership in a clear and actionable manner.
20. Support business planning, forecasting, and commercial reviews through data analysis.
21. Identify opportunities to improve data availability, reporting efficiency, and analytical capabilities.
22. Recommend new KPIs and measurement frameworks aligned with commercial objectives.
23. Stay current with emerging BI technologies, visualization techniques, and analytics best practices.

1. Bachelor’s degree in Statistics, Mathematics, Computer Science, Data Science, Business Analytics, Economics, Information Systems, or a related field.
2. Professional certifications in Business Intelligence, Data Analytics, or Data Visualization are an added advantage.
3. Minimum of 3–5 years’ experience in Business Intelligence, Commercial Analytics, or Data Analytics.
4. Experience supporting commercial, sales, marketing, customer growth, or retention functions.
5. Demonstrated experience developing and maintaining enterprise dashboards.
6. Experience working with large and complex datasets from multiple systems.
7. Experience within telecommunications, fintech, energy, FMCG, or subscription-based businesses is an advantage.
8. Advanced SQL for querying and manipulating data.
9. Strong Power BI development skills, including DAX, Power Query, data modelling, and report optimization.
10. Experience with Tableau, Looker, or similar BI platforms is desirable.
11. Proficiency in Microsoft Excel (advanced functions, Power Pivot, Power Query).
12. Familiarity with Python or R for data analysis and automation is an added advantage.
13. Experience with ETL processes and data warehousing concepts.
14. Understanding of APIs and data integration techniques is desirable.
15. Knowledge of CRM and ERP reporting environments is advantageous.
16. Strong analytical and critical thinking skills.
17. Commercial acumen with the ability to translate data into business insights.
18. Excellent problem-solving capability.
19. High attention to detail and accuracy.
20. Strong communication and presentation skills.
21. Ability to influence decision-making using data.
22. Proactive and self-driven.
23. Ability to manage multiple priorities in a fast-paced environment.
24. Collaborative team player with strong stakeholder management skills.