Data Analyst – Offline Brand & Merchant Growth (Marketing)

Kredivo; Daerah Khusus Ibukota Jakarta; On-site; IDR 200.000.000 - 300.000.000; Full time

Job summary

A leading fintech company in Jakarta is looking for a Data Analyst to support its offline expansion initiatives. The role includes data analysis, dashboard development, and cross-functional collaboration to provide actionable insights and ensure effective marketing strategies. Ideal candidates have a strong analytical background and experience with data visualization tools.

Qualifications

• 2–4 years of experience in Data Analytics, ideally in marketing, retail, or OOH performance measurement.
• Comfortable working with multiple stakeholders and large datasets.
• High attention to detail.

Responsibilities

• Analyze offline merchant performance, including store-level GMV uplift and AOV changes.
• Build and maintain SQL-based dashboards to monitor offline and regional performance.
• Translate quantitative analyses into clear insights for business and management teams.

Skills

SQL

Data visualization tools (Metabase, Power BI, Tableau, Google Data Studio)

Strong Excel/Google Sheets capability

Geolocation or spatial data handling

A/B testing knowledge

Analytical rigor

Business acumen

Education

Bachelor’s degree in Statistics, Mathematics, Economics, Business Analytics, or related fields

Job description

We are looking for a Data Analyst to support Kredivo’s offline expansion growth initiatives, including exhibitions, in-store activations, merchant branding, and OOH (Out-of-Home) projects. This role will focus on building, maintaining, and interpreting performance tracking dashboards, and ensuring every initiative’s effectiveness is measurable, comparable, and scalable. The ideal candidate is a structured thinker who can bridge data analysis and business impact, comfortable working with large datasets, and cross-functional teams like Data Science, Business Development, Growth and Brand.

Key Responsibilities

1. Data Analysis & Measurement

• Analyze offline merchant performance, including store-level GMV uplift, AOV changes, activation impact, and regional trends.
• Create post-activation and campaign evaluation reports with actionable recommendations.
• Develop standardized frameworks to measure ROI, payback period, and merchant-level success indicators.
• Normalize data from multiple measurement systems.

2. Dashboard Development & Automation

• Build and maintain SQL-based dashboards to monitor offline and regional performance.
• Automate manual data collection and reporting processes for activations, branding, and merchant metrics.
• Ensure alignment of offline data pipelines with the central data infrastructure.

3. Branding Rationalization & Analytics

• Evaluate OOH investment efficiency and help prioritize placements using data-driven insights.

4. Cross-Functional Collaboration

• Collaborate with BD, Sales, Growth, and Data Science teams to align measurement frameworks and ensure data consistency.
• Provide fast-turn insights for pilot activations, new category exploration, and regional growth experiments.
• Support offline marketing planning by identifying underperforming regions or categories
• through data-driven diagnosis.

5. Insight Reporting & Storytelling

• Translate quantitative analyses into clear, compelling insights for business and management teams.
• Build structured presentations and visual summaries that highlight findings, anomalies, and strategic opportunities.
• Present insights regularly to Brand and Management teams to guide decision-making.

Qualifications

• Bachelor’s degree in Statistics, Mathematics, Economics, Business Analytics, or related fields.
• 2–4 years of experience in Data Analytics, ideally in marketing, retail, or OOH performance measurement.
• Proficiency in SQL, data visualization tools (Metabase, Power BI, Tableau, Google Data Studio).
• Strong Excel/Google Sheets capability for quick analysis and pivoting.
• Experience handling geolocation or spatial data (heat maps, radius analysis) is a plus.
• Familiarity with A/B testing, uplift modeling, and ROI frameworks.
• Comfortable working with multiple stakeholders and large datasets.
• High attention to detail, analytical rigor, and business acumen.