Product Analyst Full-time 2024

Job Description
Cho Tot is seeking a dynamic and analytical Product Analyst to join our team. The ideal candidate will play a critical role in shaping our products by analyzing market trends, user behavior, and product performance. You will be instrumental in providing insights that drive product development and strategy, ensuring our products meet user needs and business objectives.
Analyze and interpret data to identify trends, patterns, and insights related to user behavior, product usage, and market dynamics.
Work closely with Product Managers to support data-driven decision-making, helping to define product metrics, product roadmaps and strategies.
Develop and manage analytical frameworks, metrics, KPIs and dashboards to monitor product performance and user engagement.
Conduct A/B testing and other experimental designs to validate hypotheses and inform product improvements.
Collaborate with cross-functional teams, including engineering, design, marketing, and sales, to implement and evaluate product initiatives.
Communicate findings and recommendations to stakeholders through clear and compelling reports and presentations.
Stay updated with industry trends, tools and best practices in product analytics and data science.
Qualifications
Bachelor's or Master's degree in Statistics, Economics, Computer Science, Engineering, or a related field.
Proven experience in product analytics, data analysis, or a related role.
Strong analytical skills with the ability to collect, organize, analyze, and disseminate significant amounts of information with attention to detail and accuracy.
Proficiency in data analysis tools (e.g., GA4, Google Tag Manager) and languages (e.g., SQL, Python, R) and experience with data visualization tools (e.g., Looker, Tableau).
Excellent problem-solving skills and the ability to think critically and strategically.
Strong communication and interpersonal skills, with the ability to convey complex data concepts in a clear and effective manner.
Experience with A/B testing, statistical modeling, and machine learning techniques is a plus.
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