At a Glance
- Tasks: Drive operational excellence and enhance the delivery experience using data-driven insights.
- Company: Join Uber Eats, a leader in food delivery with a dynamic team culture.
- Benefits: Competitive salary, collaborative environment, and opportunities for professional growth.
- Other info: Work in a vibrant office environment with excellent career advancement opportunities.
- Why this job: Be at the forefront of solving complex problems and making a real impact.
- Qualifications: STEM or Economics degree, 3+ years in operations/analytics, strong data analysis skills.
The predicted salary is between 60000 - 75000 £ per year.
Uber Eats delivers millions of orders each week across the UK. Behind every delivery lies a sophisticated network of processes and algorithms designed to keep our operations running smoothly. These systems tackle challenges such as determining which merchants to show each customer, assigning the right courier to each order, and dynamically balancing customer demand with courier supply in real time. In this role within the UK Operations team, you’ll be at the heart of solving these complex problems. Leveraging data‑driven insights, you'll collaborate closely with cross‑functional teams—including Commercial, Finance, Data Science, and Product—to drive operational excellence and deliver an exceptional experience for both customers and couriers.
What you will do:
- Own key aspects of our UK operations – including courier trip pricing, courier supply management/incentives and delivery experience.
- Partner with global product teams to shape, test, and launch new features (e.g. new incentive structures, dispatch algorithms).
- Use data‑driven analysis to identify opportunities to improve our operations, and bring these opportunities to life through experimentation and continuous optimisation.
- Build and optimise UK marketplace processes to ensure operational excellence (e.g. ensuring we have the right amount of courier supply).
What you will need:
- Quantitative degree in STEM, Economics or similar.
- 3+ years experience in operations/analytics/product.
- Strong commercial mindset with the ability to build compelling business cases to support recommendations.
- Robust data analysis and technical skills, including advanced SQL to source data from large, complex data sources.
- Able to use Python to perform data analysis (e.g. data manipulation, regression modelling).
- Excellent communication skills (both written and spoken).
- Experience working with a wide range of functional stakeholders (Product, Engineering, Commercial, Finance, Legal).
Offices continue to be central to collaboration and Uber's cultural identity. Unless formally approved to work fully remotely, Uber expects employees to spend at least half of their work time in their assigned office. For certain roles, such as those based at green‑light hubs, employees are expected to be in‑office for 100% of their time. Please speak with your recruiter to better understand in‑office expectations for this role.
*Accommodations may be available based on religious and/or medical conditions, or as required by applicable law. To request an accommodation, please reach out to accommodations@uber.com.
Senior Marketplace Manager employer: Uber
Uber Eats is an exceptional employer that fosters a dynamic and collaborative work culture, where innovation thrives and employees are empowered to make impactful decisions. With a strong focus on employee growth, you will have access to extensive training and development opportunities, allowing you to enhance your skills in a fast-paced environment. Located in the heart of the UK, our offices serve as vibrant hubs for teamwork and creativity, ensuring that every team member contributes to delivering outstanding experiences for customers and couriers alike.
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We think you need these skills to ace Senior Marketplace Manager
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Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
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Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
