Senior Data Analyst
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What you'll do
- Own a logistics problem domain end-to-end, framing ambiguous problems and delivering analytical solutions that drive measurable improvements in cost, efficiency, and service performance.
- Act as a thought partner to business and domain leads, shaping problem statements, challenging assumptions, and co-developing data-driven solutions to high-impact logistics challenges.
- Apply advanced analytical methods, including simulation, optimization, and statistical modeling, to solve complex problems such as fleet sizing, routing, staffing, and demand planning.
- Determine causal impact in operational environments, designing and analyzing experiments (e.g., cluster, switchback) and applying causal inference methods (e.g., DiD, synthetic controls) to inform business decisions.
- Build and scale data products and analytical tools, leveraging modern data stacks and agentic AI workflows to enable deep dives, self-serve analytics, and faster decision-making.
- Drive exploratory and root cause analyses, identifying performance drivers and uncovering opportunities for optimization across the logistics value chain.
- Collaborate cross-functionally with data and engineering teams, contributing to data modeling, metric definitions, and scalable solutions that accelerate time-to-insight.
- Communicate with clarity and influence, translating complex analyses into actionable recommendations and driving alignment across technical and business stakeholders.
What they're looking for
- Bachelor’s degree in a quantitative field (e.g., Statistics, Operations Research, Mathematics, Computer Science, Engineering) or equivalent practical experience, with 5–8 years of experience in analytics or data science.
- Proven experience in logistics, supply chain, or operations analytics, with a track record of solving problems such as fleet sizing, routing, staffing, or demand planning and delivering measurable business impact.
- Strong technical proficiency in SQL and Python, with experience working with large-scale datasets (e.g., writing efficient queries, optimizing performance, working with NoSQL or distributed data systems).
- Experience working with modern data platforms, preferably within the Google Cloud ecosystem (e.g., BigQuery, Vertex AI, Google Colab, Google Sheets), or similar cloud-based data stacks.
- Experience applying advanced analytical methods, including simulation, optimization, and statistical modeling to real-world business problems.
- Experience in causal inference and experimentation, including designing and analyzing experiments (e.g., A/B, cluster, switchback) and applying quasi-experimental methods (e.g., DiD, synthetic controls).
- Strong problem-solving and problem structuring skills, with the ability to independently navigate ambiguity and translate business questions into robust analytical approaches.
Summarised by NextRaise from the employer’s description, which follows in full below.
Full description from employer
Company Description
foodpanda is part of the Delivery Hero Group, the world’s pioneering local delivery platform, our mission is to deliver an amazing experience—fast, easy, and to your door. We operate in around 65 countries worldwide. Headquartered in Berlin, Germany. Delivery Hero has been listed on the Frankfurt Stock Exchange since 2017 and is part of the MDAX stock market index.
Job Description
As a Senior Data Analyst (Logistics Analytics), you will leverage your expertise to directly impact the growth of our 16 markets by delivering actionable insights and advanced analytics solutions. In this role, you’ll work closely with senior stakeholders, mentor junior analysts, and shape the analytics function within one of our functional analytics teams. This is a high-visibility position that plays a pivotal role in data-driven decision-making.
- Own a logistics problem domain end-to-end, framing ambiguous problems and delivering analytical solutions that drive measurable improvements in cost, efficiency, and service performance.
- Act as a thought partner to business and domain leads, shaping problem statements, challenging assumptions, and co-developing data-driven solutions to high-impact logistics challenges.
- Apply advanced analytical methods, including simulation, optimization, and statistical modeling, to solve complex problems such as fleet sizing, routing, staffing, and demand planning.
- Determine causal impact in operational environments, designing and analyzing experiments (e.g., cluster, switchback) and applying causal inference methods (e.g., DiD, synthetic controls) to inform business decisions.
- Build and scale data products and analytical tools, leveraging modern data stacks and agentic AI workflows to enable deep dives, self-serve analytics, and faster decision-making.
- Drive exploratory and root cause analyses, identifying performance drivers and uncovering opportunities for optimization across the logistics value chain.
- Collaborate cross-functionally with data and engineering teams, contributing to data modeling, metric definitions, and scalable solutions that accelerate time-to-insight.
- Communicate with clarity and influence, translating complex analyses into actionable recommendations and driving alignment across technical and business stakeholders.
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!
Qualifications
- Bachelor’s degree in a quantitative field (e.g., Statistics, Operations Research, Mathematics, Computer Science, Engineering) or equivalent practical experience, with 5–8 years of experience in analytics or data science.
- Proven experience in logistics, supply chain, or operations analytics, with a track record of solving problems such as fleet sizing, routing, staffing, or demand planning and delivering measurable business impact.
- Strong technical proficiency in SQL and Python, with experience working with large-scale datasets (e.g., writing efficient queries, optimizing performance, working with NoSQL or distributed data systems).
- Experience working with modern data platforms, preferably within the Google Cloud ecosystem (e.g., BigQuery, Vertex AI, Google Colab, Google Sheets), or similar cloud-based data stacks.
- Experience applying advanced analytical methods, including simulation, optimization, and statistical modeling to real-world business problems.
- Experience in causal inference and experimentation, including designing and analyzing experiments (e.g., A/B, cluster, switchback) and applying quasi-experimental methods (e.g., DiD, synthetic controls).
- Strong problem-solving and problem structuring skills, with the ability to independently navigate ambiguity and translate business questions into robust analytical approaches.
Additional Information
What we offer:
- A dynamic and challenging work environment.
- A company committed to developing you personally and professionally.
- A great working atmosphere with regular company and team events.
- A vibrant and international team committed to diversity and inclusion.
- Responsibility from day one in a fast growing and global company.
foodpanda is operated by Delivery Hero Group (“DH Group”) - the world’s leading local delivery platform, operating in 70+ markets across Asia, Europe, Latin America, the Middle East, and Africa. Delivery Hero started as a food delivery service in 2011 and now employs 40,000+ people globally. Additionally, Delivery Hero is pioneering quick commerce, the next generation of e-commerce, aiming to bring groceries and household goods to customers in under one hour and often in 20 to 30 minutes. Headquartered in Berlin, Germany, Delivery Hero has been listed on the Frankfurt Stock Exchange since 2017.
In July 2024, Delivery Hero SE merged three of its market-leading food delivery businesses, foodora and Yemeksepeti in Europe, and foodpanda in Asia. All three businesses now make up the second-largest organization within the Delivery Hero Group, and leading food and QCommerce delivery in 17 markets in both regions.
Company
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