Staff Data Analyst

As a Staff Data Analyst within the Fresh SCM Automation team, you will drive strategic decision-making by solving complex supply chain and inventory optimisation challenges through advanced analytics. The team is responsible for building scalable analytical frameworks, products, and data science capabilities that improve product availability while optimising inventory and operational costs. You will work closely with Product, Supply Chain, Forecasting, and Engineering teams to influence key business decisions and develop data-driven solutions that support Coupang's rapidly growing Fresh business.

Responsibilities:

• Lead end-to-end analysis of complex supply chain and inventory management problems.
• Develop analytical frameworks and decision models to improve forecasting accuracy, replenishment efficiency, and inventory optimisation.
• Partner with Product, Engineering, Supply Chain, and Business stakeholders to identify improvement opportunities and define success metrics.
• Build scalable dashboards, KPIs, and automated reporting solutions to support business visibility and decision-making.
• Design and execute simulations and scenario analyses to evaluate operational strategies and business trade-offs.
• Utilise SQL, Python, R, and visualisation tools to extract, analyse, and structure large datasets.
• Drive root-cause analysis and generate actionable recommendations for senior leadership.
• Mentor analysts and contribute to elevating analytical standards across the organisation.

Requirements:

• Problem Solver at Heart: Passionately approaches complex or undefined problems with curiosity, analytical thinking, and a drive to find novel solutions.
• End-to-End Ownership: Proven track record of independently taking projects from initial concept through execution and delivery with minimal supervision.
• Domain and Field Experience: 8+ years of experience leveraging data to drive strategic decisions in Data Analytics, Business Analytics, Supply Chain Analytics, or a related field.
• Education: Bachelor's degree in Statistics, Mathematics, Economics, Engineering, Computer Science, Operations Research, or a related quantitative discipline.
• Advanced SQL and Data Wrangling: Deep expertise in SQL with extensive experience querying, manipulating, and extracting insights from large-scale enterprise datasets.
• Statistical Programming: Proficiency in Python and/or R for data manipulation, exploratory analysis, and statistical modelling.
• Executive Visualisation and Reporting: Mastery of business intelligence and visualisation tools (e. g., Tableau, Power BI) to translate complex data into clear, intuitive dashboards and executive-ready reporting.
• Stakeholder Influence and Communication: Outstanding ability to translate technical findings into actionable business insights and influence senior stakeholders across functions, backed by professional business-level English communication skills.

Preferred Qualifications:

• Domain Expertise: Specialised background in eCommerce, Retail, Supply Chain, Inventory Management, Logistics, or Operations Research.
• Advanced Modelling and Optimisation: Hands-on experience developing optimisation models, forecasting frameworks, or simulation-based analyses to solve operational bottlenecks.
• Machine Learning and Experimentation: Familiarity with predictive analytics, machine learning algorithms, and experimentation methodologies (A/B testing, causal inference).
• Leadership and Mentorship: Demonstrated ability to lead large-scale analytical initiatives and mentor junior and mid-level analysts.
• Global Collaboration: Proven success working collaboratively with cross-functional, globally distributed teams.
• Advanced Degree: Master's degree or PhD in a quantitative or engineering discipline.

Skills

Python, R, SQL, forecasting, inventory, logistics, optimization, supply chain