Live opening · Posted 5 days ago

Data Analyst (Quick Commerce & Partnerships)

DeliveryHero · Kuala Lumpur, , Malaysia
Smartrecruiters Hybrid Full-time
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At a glance

The key details from the original listing.

Posted 5 days ago
CompanyDeliveryHero
LocationKuala Lumpur, , Malaysia
Job typeFull-time
Work modeHybrid
SourceSmartrecruiters
Listed5 days ago

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About the role

Description supplied by the original job listing.

As a Data Analyst in the Quick Commerce & Partnerships Analytics team, you will be part of our mission to drive impactful decisions and incremental value across our 16 markets. You'll support the team by conducting deep-dive analyses, maintaining data consistency and providing high-quality strategic insights that drive decisions on key quick commerce levers — from dark store expansion and assortment changes to delivery fee adjustments and discounting. This is a foundational role offering the opportunity to grow technical skills, gain exposure to high-impact projects, and learn from experienced data professionals who work on big problems at a global scale, leveraging the latest AI tools and analytical techniques.
Quick Commerce Analysis: Utilize analytical methodologies ranging from data modeling to descriptive/predictive/prescriptive analytics in order to measure incremental impact and make actionable recommendations on quick commerce investments (e.g. dark store expansion, assortment changes, delivery fee adjustments, discounting), customer conversion funnel, cost/margin optimization, and tactical execution of quick commerce initiatives.
Data Modeling & Measurement: Build and refine measurement frameworks and metric definitions for key quick commerce initiatives (e.g. Shops, dark store performance, fulfillment/delivery metrics); support the development of SQL models to implement frameworks and transform massive datasets into actionable insights using tools like BigQuery (SQL), Excel, and dbt.
Strategic Reporting & Visualization: Build compelling, user-friendly data assets including both traditional dashboards (e.g. Looker, Tableau) and agentic solutions (e.g. root-cause analysis agents for delivery delays or stockouts) that facilitate decision-making for business operators and leaders.
Collaboration & Stakeholder Partnership: Collaborate with quick commerce, operations, and supply chain partners to understand strategic objectives, recommend analytics solutions, and present insights effectively. Also, work closely with senior analysts and team leads, learning from their approach to data modeling, visualization, and storytelling.
Data Quality & Tracking: Monitor data quality and participate in QA processes to ensure consistency across all reporting metrics.
AI-Driven Analytics & Automation: Evaluate and implement AI-powered solutions that transform how quick commerce analytics operates — including agentic workflows (e.g. root-cause analysis agents, automated anomaly detection on delivery/fulfillment metrics), LLM-assisted insight generation, and prompt-engineered pipelines. Help translate repeatable analyst workflows into scalable AI tools, and share knowledge across the team.
Find out more about our Data Analytics folks here:
Turn insights into impact!
Looking for a career in data analytics? This could be the opportunity for you!
Bachelor's degree in Statistics, Mathematics, Economics, Computer Science, or a related field.
Overall 2-4 years of experience in data analytics. Experience supporting Quick Commerce, Operations, Supply Chain, or Commercial teams (online or offline retail), or similar, is an advantage.
2+ years of proficiency in SQL and experience with at least one data visualization tool (e.g., Looker, Tableau). Familiarity with dbt is a plus.
Strong communication skills, with an ability to present findings in a clear and concise way to various levels of business partners.
A team-oriented mindset with a willingness to learn and take on new challenges.
Solid background in statistical analysis and data modeling is an advantage.
Interest in AI solutions and their applications in analytics is an advantage.

Employment type
Full-time

Work arrangement
Hybrid

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