
Ecommerce & Data Analyst Intern
- Singapore
- Training
- Full-time
- Drive business insights through comprehensive data analysis of key metrics (revenue, customer behaviour, marketing performance), utilizing SQL and Power BI to create automated reports and visualizations for stakeholder decision-making.
- Design and optimize machine learning models for predictive analytics while working with large datasets to identify patterns and validate hypotheses for improved business outcomes.
- Enhance data infrastructure by optimizing processes, maintaining documentation, and implementing best practices in data analysis, while providing training and knowledge transfer across teams.
- Currently pursuing a Bachelor's degree in Data Analytics, Data Science, Computer Science, Information Systems, Statistics, or related field.
- Strong programming fundamentals with proficiency in SQL and Python, including experience with database operations.
- Hands-on experience with data visualization tools (PowerBI or Tableau) and basic understanding of statistical analysis and machine learning concepts.
- Demonstrated analytical and problem-solving abilities with strong attention to detail.
- Excellent interpersonal and team collaboration skills with proven ability to meet deadlines.
- Previous internship or project experience in data analysis.
- Hands on experience in leveraging database and data query technologies (e.g. Redshift, PostgreSQL, Snowflake, etc).
- Experienced with Python libraries such as NumPy, Pandas, scikit-learn.
- Experience with data pipeline tools and ETL processes.
- Strong communication and presentation skills.
- The Intern will gain a comprehensive understanding of how data analytics, machine learning, and process optimization can drive growth and improve customer engagement.
- This will also enhance intern ability to leverage data effectively, improve business performance, and support strategic decision-making within an organization.
- New dashboard development for analysis of customer purchase behaviour that can help business teams to define future strategies
- Automation of existing reporting processes to reduce manual effort and risk of data discrepancies, improving reporting efficiency
- Optimize machine learning algorithms for revenue forecasting to improve accuracy and help in decision making