About the company
Join a fast-paced product analytics team as an early-career data professional and gain hands-on experience working with real product data. You will support analysis across conversion funnels, experimentation, user behavior, and key product performance metrics. The role offers exposure to data-driven product strategy and experiment-led decision-making in a global, technology-focused environment.
Responsibilities
- Support the development and analysis of user conversion funnels, identifying key drop-off points, behavioral patterns, and opportunities to improve the user experience.
- Assist with A/B test analysis by extracting experiment data, validating cohort allocation through sanity checks, calculating uplift metrics, and summarizing findings.
- Build and maintain dashboards tracking important product metrics, including click-through rates, conversion rates, unique visitors, and page views.
- Respond to ad-hoc analytical requests from product teams, including user segmentation, feature adoption analysis, and campaign performance assessments.
- Write, optimize, and maintain SQL queries used in recurring and scheduled data pipelines.
- Assist with data quality monitoring and help identify potential inconsistencies or issues in analytical datasets.
- Translate analytical findings into clear summaries, visualizations, and actionable insights for product stakeholders.
- Work closely with senior analysts and product teams to understand business questions and translate them into structured analytical approaches.
- Develop practical knowledge of product analytics, experimentation, user behavior, and data-driven product strategy.
Requirements
- Currently pursuing or recently completed a Bachelor's or Master's degree in Statistics, Computer Science, Economics, Data Science, or another quantitative discipline.
- Previous internship experience in product analytics, data analysis, business intelligence, or a related field is preferred.
- Strong curiosity and analytical thinking, with the ability to investigate trends, identify patterns, and explain findings clearly.
- Professional fluency in both English and Mandarin is required to coordinate effectively with international partners and stakeholders.
- Understanding of A/B testing fundamentals, including hypothesis testing, p-values, confidence intervals, cohort allocation, and uplift measurement.
- Strong logical reasoning, attention to detail, and the ability to work independently in a fast-moving environment.
- Demonstrated willingness to learn, with genuine curiosity about product strategy, user behavior, and data-driven decision-making.
- Proficiency in at least one of the following areas:
- SQL: ability to write complex queries using CTEs, window functions, subqueries, and related techniques.
- Programming: experience with Python or R for data manipulation and analysis.
- Data visualization: familiarity with tools such as DataWind, Tableau, or Power BI.
- Experience with event tracking or behavioral analytics platforms such as Sensors, Mixpanel, or Google Analytics is an advantage.
- Familiarity with Airflow or other data scheduling and orchestration tools is a plus.
- Interest in cryptocurrency, fintech, blockchain, or digital assets is beneficial.
- Exposure to large-scale data environments such as Hive or Spark is a plus.
Conditions
- 3–6 month structured internship designed for current university students and recent graduates.
- Hands-on experience working on real product analytics projects alongside experienced data professionals.
- Exposure to conversion analysis, A/B testing, dashboards, user behavior analytics, and large-scale data infrastructure.
- Opportunities to develop practical technical, analytical, and product strategy skills.
- Networking and professional development opportunities within a global technology environment.
- Opportunity to collaborate with experienced professionals and international stakeholders.
- Fast-paced, innovative environment with exposure to unique product and data challenges.
- Opportunities for continued learning and potential career development.
- Competitive compensation and applicable company benefits, subject to local employment terms and applicable law.
- Remote work arrangement, subject to the requirements and working model of the relevant business team.