Data Leader

Define the Data strategy and roadmap, ensuring scalable data capabilities to support product and marketing needs.

Build and deploy predictive models, such as predictive Lifetime Value (pLTV), revenue forecasting, and user behavior prediction.

Apply data analysis and modeling techniques to improve the accuracy and reliability of predictions.

Develop and optimize data models, analytical frameworks, and measurement methodologies to support product growth and monetization.

Monitor model performance, validate predictions, and continuously improve models based on new data and evolving business needs.

Lead the Data Analytics team in delivering high-quality analysis, dashboards, and insights that support product and business decisions.

Establish consistent definitions for key business and product metrics, including acquisition, activation, retention, engagement, conversion, revenue, and Lifetime Value (LTV).

Guide analyses of user behavior, product funnels, cohort performance, monetization opportunities, and marketing effectiveness.

Promote rigorous experimentation practices, including A/B testing, hypothesis validation, and measurement of product and growth initiatives.

Ensure analytics outputs go beyond reporting to identify root causes, opportunities, and actionable next steps.

Lead the development of scalable, reliable, and maintainable data infrastructure to support analytics and business needs.

Oversee data pipelines, data integration, data modeling, data warehouse architecture, and data quality monitoring.

Oversee the integration and effective use of marketing analytics platforms, attribution tools, tracking systems, and relevant marketing technology solutions.

Ensure consistency and reliability in campaign tracking, attribution, conversion measurement, and marketing performance data.

Partner with Marketing/Growth teams to improve visibility into campaign performance, user quality, acquisition efficiency, and downstream revenue.

Foster collaboration across Data, Product, Marketing/Growth, Monetization, and Engineering teams.

Develop a scalable operating model that balances shared data capabilities with the specific needs of individual product teams.

8+ years of experience in Data Analytics, Business Intelligence, Data Engineering, or a related data field, with relevant experience leading projects, teams, or cross-functional initiatives.

Strong understanding of the Martech industry, particularly mobile app marketing, attribution, tracking systems, and monetization.

Strong proficiency in SQL, statistical analysis, data modeling, and data-driven problem-solving.

Experience with marketing analytics platforms and data integration to measure user acquisition, campaign performance, and business outcomes.

Experience developing predictive models such as pLTV, revenue forecasting, or user behavior prediction is a strong advantage.

Strong strategic thinking, stakeholder management, and cross-functional collaboration skills, with a focus on building scalable data capabilities and delivering business impact.

Experience leading data projects or initiatives, with the ability to prioritize tasks, allocate resources, and ensure effective execution.