Lead Data Analyst

We are looking for a Lead Data Analyst at Flip. You will be responsible for directly managing data discovery and insights generation thereby leading to marketing and product improvement. In this role, you will also be expected to collaborate with Data Engineers to improve and enrich existing state of data to meet current as well as possible future use cases.

Key Responsibilities:

• Lead key strategic initiatives ensuring high-quality of analysis and insights

• Be able to coach and guide junior members, and be able to drive a culture of ownership, curiosity and innovation

• Develop and refine analytics frameworks for marketing campaigns, customer segmentation, and product performance

• Partner with marketing and product teams to identify key metrics and provide deep analytical insights

• Build and maintain dashboards and reporting tools to monitor key business KPIs

• Design, execute and iterate A/B testing and causal impact analysis to measure campaign effectiveness

• Optimize user acquisition, retention, and engagement strategies using data-driven approaches

• Work with data engineering teams to ensure data availability, accuracy, and integrity

• Present insights and recommendations to senior leadership for data-driven decision-making

Requirements:

• 5+ years of experience in data analytics, preferably in marketing or product analytics

• Strong SQL skills and experience with data visualization tools (e.g., Redash, Looker, Power BI, Tableau)

• Proficiency in Python for data analysis and modeling

• Experience with A/B testing, cohort analysis, and predictive modeling.

• Hands-on experience working with large datasets and cloud-based data platforms (e.g., BigQuery, Snowflake) [GCP preferred]

• Ability to translate complex data findings into clear business insights

• Strong stakeholder management skills and the ability to communicate technical concepts to non-technical teams

• Prior experience in leading and mentoring analysts is preferred

Nice to Have:

• Experience in a fintech or high-growth tech environment

• Familiarity with marketing attribution models and customer lifecycle analytics

• Knowledge of experimentation frameworks and causal inference methods