Data Analytics Specialist

• Business insight and decision support: Translate strategic and operational questions into clear analyses, dashboards, reports, and recommendations for leadership and functional teams.
• KPI and metrics ownership: Define, document, and govern business metrics across fuel consumption, transaction activity, customer adoption, fleet performance, station coverage, invoicing, product usage, savings, churn, and operational efficiency.
• Dashboard and reporting delivery: Build reliable self-service dashboards for executives, product, sales, finance, operations, customer success, and country or regional teams.
• Customer and product analytics: Analyze user journeys, feature adoption, customer cohorts, fleet behavior, transaction trends, fuel limits, budget usage, and drop-off points to guide product and growth decisions.
• Operations and finance analytics: Support reconciliation, invoicing, station performance, wallet movement, service usage, cost analysis, revenue tracking, and profitability insights.
• Fraud and anomaly insight: Partner with product, operations, and data engineering to identify unusual fuel patterns, tampering indicators, policy exceptions, and monitoring rules that improve trust and control.
• Experimentation and forecasting: Design analyses for pilots, pricing, campaigns, product launches, and operational changes; support forecasting for consumption, transactions, customer demand, and station utilization.
• Data storytelling: Present insights clearly, explain trade-offs, quantify impact, and convert analysis into practical recommendations and action plans.
• Data quality partnership: Work with data engineering to improve source data, metric definitions, documentation, dashboard reliability, and analytics-ready datasets.
• Analytics mentorship: Set standards for analysis quality, dashboard design, metric governance, and stakeholder communication while mentoring less experienced analysts.

Requirements

Required qualifications

• 5+ years of experience in data analytics, business intelligence, product analytics, revenue analytics, operations analytics, or a similar analytical role.
• Advanced SQL skills with the ability to independently extract, transform, join, validate, and analyze complex data from multiple domains.
• Strong experience building dashboards and data products using Power BI, Tableau, Looker, Metabase, Superset, or similar BI tools.
• Strong understanding of KPI design, metric definitions, funnel analysis, cohort analysis, segmentation, trend analysis, forecasting, and root-cause analysis.
• Ability to convert ambiguous business questions into analytical plans, structured hypotheses, and actionable recommendations.