Data Analyst (Fresh Graduate)

🎓 Graduate With a Degree. Leave With Real Data Experience.

Your first job can be more than an entry-level title.

Start your career working with real data, real business problems, modern AI tools, and experienced mentors — while building the technical skills companies actually look for in data professionals.

Fresh graduates are welcome. No years of experience required. If you know SQL, understand data, and have the curiosity to keep learning, we'll help you take the next step.

Key responsibilities

• Data Extraction & Wrangling — write efficient SQL queries across our cloud data warehouse (Google BigQuery) to extract, validate, and transform multi-source business data.

• Exploratory & Diagnostic Analysis — investigate operational workflows, transaction lifecycles, and unit economics to diagnose root causes and identify optimization opportunities.

• Reporting & Visualisation — build and maintain clean data reports, performance tracking scorecards, and interactive dashboards to monitor key operational and financial metrics.

• Stakeholder Collaboration — partner with cross-functional teams (Operations, Product & Tech, Finance) to establish clear metric definitions and maintain data integrity.

• Workflow Automation & Tooling — leverage Python and modern developer tools to automate recurring analytical pipelines and data hygiene checks.

Job Requirements

• Minimum Diploma/Bachelor's degree in Data Science, Computer Science, Statistics, Mathematics, Physics, Engineering, Economics, or another quantitative discipline.

• Fresh graduates and entry-level candidates are welcome if you have strong data, analytical, or quantitative training.

• Strong SQL fundamentals — comfortable with queries, multi-table joins, aggregations, window functions, and data transformations.

• Foundational Python knowledge — familiarity with Python for data manipulation using tools such as pandas and NumPy.

• Basic understanding of data analysis, statistics, and data visualisation.

• Familiarity with AI tools and LLM-based assistants for coding, analysis, prototyping, or productivity.

• Strong problem-solving and analytical thinking.

• High attention to detail and commitment to data accuracy.

• Ability to validate assumptions and question data when something does not look right.

• Good communication skills and the ability to explain technical findings in clear, simple language.