Data Product Specialist

Maya is looking for detail-oriented and data-driven Data Product Manager to join our dynamic team and be part of a growing Fintech in the Philippines. The ideal candidate will bridge the gap between business, product, and data science teams, ensuring the development of data-driven solutions that meet business objectives. As a Data Product Manager, you will analyze data, define product metrics and analytics, and support decision-making by delivering actionable insights to drive product growth and optimization.

NATURE OF WORK

• Data Product Manager role involves analyzing large datasets to uncover trends, define product analytics frameworks (including funnel analytics), and provide actionable insights that drive product optimization and strategy. 
• Collaborating with cross-functional teams, the analyst bridges data science, product management, and business needs to define key metrics, AI strategies for each product, and data requirements. 
• The role includes designing A/B tests, maintaining dashboards, and leveraging AI and machine learning techniques to enhance decision-making and product performance. 
• Focused on improving user experience and retention, the analyst also ensures data quality, solves complex business problems, and supports leadership with data-driven recommendations in a dynamic, collaborative, and fast-paced environment. 
• Defining and building data products within the Enterprise Product portfolios by wgclosely with all stakeholders within the company.

REQUIRED QUALIFICATIONS

• Critical thinking and problem-solving skills with attention to detail.
• Bachelor’s degree in Data Science, Statistics, Computer Science, Economics, or a related field.  
• Proven experience in data analysis, preferably within a product or technology-focused organization.
• Minimum of 5 years in product management or a related role, with a focus on platform or API development.
• Understanding of statistical methods and concepts to interpret data accurately
• Proficiency in SQL, data analysis tools (e.g., Tableau, Power BI), programming languages like Python or R and analytics platforms (e.g., Google Analytics).
• Experience with A/B testing frameworks and tools (e.g., Split.io or Optimizely).
• Knowledge of machine learning techniques and their applications in product analytics.
• Passionate with AI and its usage across changing customers lifestyle
• Strong understanding of API architecture, integration, and data exchange protocols. Proficiency in software development life cycle (SDLC) and Agile methodologies.
• Demonstrated ability to analyze data, derive actionable insights, and drive data-informed decisions.
• Proven experience managing complex projects, with a track record of delivering on time and within scope.
• Excellent verbal and written communication skills, with the ability to effectively convey technical concepts to non-technical stakeholders.