Job Responsibilities

Data Analysis:

• Perform detailed data analysis and interpretation to identify trends, patterns, and insights.
• Utilize statistical tools and techniques to extract actionable insights from large and complex datasets.
• Conduct ad-hoc analysis to address specific business questions and challenges.

Machine Learning and Predictive Analytics:

• Develop machine learning models to support various business functions, enhancing predictive/ prescriptive capabilities and operational efficiency.

Reporting and Visualization:

• Develop and maintain regular PBI reports and dashboards to track key business metrics and facilitate informed decision-making
• Present findings and insights to stakeholders through clear and compelling visualizations.
• Train & support business users on building dashboards/ visualizations on their own

Collaboration:

• Work closely with various departments to understand their data needs, pain points and provide analytical support.
• Collaborate with Digital Technology and Data Engineering teams to improve data infrastructure and accessibility.
• Participate in cross-functional projects to drive data-driven decision-making.

Strategic Insights:

• Provide recommendations based on data analysis to support strategic planning and decision-making.
• Identify opportunities for process improvements and operational efficiencies.
• Monitor industry trends and competitive landscape to inform business strategies.

Documentation:

Document all methodologies and results to ensure clarity and reproducibility of analyses.

Requirements

Education:

• Bachelor’s in Data Science, Computer Science, Statistics, Mathematics, Business Analytics or a related field.

Experience:

• 1-4 years proven experience as a Data Analyst or similar role, preferably in the Retails, F&B or FMCG industry.
• Familiarity with database management systems, data manipulation, and data cleaning techniques.
• Familiarity with below Tech Stacks:
• Python
• PowerBI
• SQL/ Non-SQL databases
• Data science stack – Pandas, Numpy, visualization packages, SciPy, Scikit Learn, Tensorflow, etc.
• Version control with git
• Google Cloud Platform
• Development stack – Streamlit, Django, Flask, FastAPI (Good to have)

Knowledge/ Skills:

• Understanding of statistics, probability, and data analysis techniques that are foundational to interpreting data sets.
• Knowledge of machine learning and predictive analytics.
• Strong problem-solving skills and ability to think critically.
• Excellent communication and collaboration & presentation skill.
• Ability to work independently and collaboratively using Scrum methodology.
• Good command of English.
• Cantonese & Mandarin capability is a plus.

Benefit package: