Full-time

As the leading Voice Assistant in Vietnam, Kiki makes it easier for Vietnamese users to enjoy a hands-free experience on multiple platforms. As a Data Analyst working at Kiki, you have a chance to make a positive impact on nearly 1M car users by leveraging the power of our data.
This role specifically focuses on data analytics to better understand our users and uncover actionable insights, as well as collaborating with the Product team to develop relevant and effective product solutions.

• Conduct analysis to obtain a better knowledge of user behavior and to find actionable product innovation insights. This can include a variety of techniques such as user profiling and predictive modeling, among others;
• Partner with the Product team to design and build metrics for monitoring the health of product features and the entire ecosystem;
• Conduct A/B testing to measure the performance of product launches and operations;
• Implement a data foundation (data pipelines, data quality, reports, and dashboards) to track our products' performance.

• Bachelor's degree in Data Science, Computer Science, Statistics, or a related field;
• At least 1+ years of experience working in the field of data analytics, preferably with experience designing and managing scalable data pipelines;
• Proficiency in data querying languages (e.g., SQL), programming languages (e.g., R, Python);
• Good communication and interpersonal skills, storytelling with data, e.g., ability to communicate data science concepts and analysis results to both technical and non-technical audiences;

• Understanding of applied statistics including experiment design and data mining techniques;
• Experience in the online consumer product or software development industries;
• Knowledge of Hadoop programming environments (e.g., Spark) is a plus;
• Exposure to data visualization tools (Tableau, Qlik, Looker, R Shiny) is a plus;
• Proactive thinking and ability to work independently while being a strong team player;
• Flexibility: you should be flexible in your tasks and do whatever is needed, ranging from dirty work like data cleaning to high-level work like system or algorithm design.