Job Description:
Objectives of this Role:
Analyze and interpret market and user data to drive business decisions and improve product offerings.
Develop and maintain robust data architecture for efficient data processing and analysis.
Present data insights in a clear, actionable manner to stakeholders across the company.
Understand and navigate the complexities of app marketing and related data restrictions.
Support product development and commercial objectives by providing data-driven insights and recommendations.
Responsibilities:
Design, implement, and manage backend data architecture to support analytics and reporting needs.
Collect, process, and analyze large datasets to extract meaningful insights about user behavior, product performance and growth roadmaps.
Create and maintain dashboards, reports, and visualizations to present data in an understandable and actionable way.
Collaborate with product, business, engineering and management teams to align data initiatives with company goals.
Stay up-to-date with the latest trends and best practices in data science, nalytics, and B2C app marketing and educate stakeholders on best practices.
Ensure compliance with data privacy regulations and best practices in data handling.
Augment the company with relevant Ai toolings to grow and scale with data insights.
Skills and Qualifications:
8+ years of proven working experience in data science, analytics, or a related field in tech/ cloud/ software domain.
Proficiency in programming languages such as Python, R, or SQL.
Experience with data visualization tools like Mixpanel, Domo or similar.
Solid understanding of backend data architecture and database management.
Ability to interpret complex data and present it in a clear, concise manner.
Familiarity with data privacy regulations and best practices.
Excellent problem-framing, problem solving and project management skills.
Excellent communication skills with proficiency in English.
Preferred Qualifications:
Experience in the B2C app companies, particularly with user data analysis.
Commercial acumen and the ability to align data insights with business objectives.
Understanding of app marketing strategies and associated data restrictions.
Knowledge of machine learning techniques and their application in business contexts.
Ability to work independently and collaboratively.
Fluency in AI-powered toolings to optimize productivity and efficiency.
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