AVP-TFE Business Insights, Experiments and Automation

The Role Summary

The AVP of TFE Business Insights, Experiments and Automation owns three core areas for TFE (Telco Financial Ecosystem): (1) experiments, (2) insight generation for TFE products, and (3) AI and automation.

TFE products include Paket Darurat (emergency credit for prepaid users), SMS Banking and other products (eg. . The role is responsible for designing statistically rigorous experiments, generating actionable insights from data, and building AI/automation solutions that enable the team to operate at high velocity.

The role requires someone who can work independently across the full experiment lifecycle: from building hypotheses using behavioral data, to calculating sample sizes and power, to running the test, to analyzing results with proper statistical methods, to making the call on whether to scale, iterate, or kill.

We operate on a self-service principle where this role owns 80%+ of analysis end-to-end, minimizing dependency on the Data team for basic queries and experiment analysis.

Responsibilities

1. Experiment Design & Statistical Analysis

• Design and run 10+ experiments per month with proper statistical methodology
• Own the full experiment lifecycle: hypothesis → power analysis → sample sizing → execution → analysis → scaling decision
• Calculate sample sizes, minimum detectable effects, and run duration before launching experiments
• Apply proper statistical methods (ie. t-tests, chi-square, confidence intervals, p-values) to determine if results are significant
• Maintain experiment tracking with proper control group management to ensure robustness of experiment results
• Build the prioritization framework (ie. ICE scoring) to ensure effective deployment of resources

2. Business Insights & Analytics

• Build and maintain dashboards for North Star metrics and experiment performance
• Conduct funnel analysis, cohort analysis, and conversion optimization
• Translate analytical findings into clear recommendations for leadership
• Document learnings to ensure that the team has a robust system to track, learn, and compound from previous learnings

3. AI & Automation

• Build automated reporting pipelines to reduce manual effort (ie. daily/weekly performance reports)
• Design AI-powered workflows for campaign personalization and audience segmentation
• Deploy self-hosted and self-developed AI/automation solutions to reduce manual effort
• Build internal tools to support process execution, and drive adoption within team and across broader company
• Drive adoption of internal AI tools (ie. ExperiLoom for experiment analysis, Palette for campaign execution)

4. Cross-Functional Collaboration

• Work with Data Analytics & Engineering for data access, pipeline development, and experiment infrastructure
• Partner with Data Science on model development (ie. propensity models, churn prediction)
• Provide insights and recommendations to leadership backed by data

Key Qualifications and Skills

1. Analytical skills and SQL proficiency: The role requires someone who can independently build hypotheses from user behavior data and design statistically rigorous experiments. This includes the ability to query and analyze data in BigQuery using SQL. Must be comfortable with statistical concepts (ie. hypothesis testing, confidence intervals, p-values, power analysis, regression)
2. Experiment experience: Proven track record designing and analyzing A/B tests at scale
3. Experiment execution: Hands-on experience with setting up experiments using available tools (ie. communication channels, SMS, app communication tools, landing pages)
4. AI capabilities: Understanding of applications of data science models in experiments and marketing
5. Communication skills: Able to explain technical findings to non-technical stakeholders. Strong stakeholder management

Nice to Have

• Background in telco, fintech, or insurance industries
• Strong interest in applying AI (LLM and traditional ML), automation, and self-hosting into professional settings