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Staff Data Scientist - Quick Commerce

Company Description

As the world’s pioneering local delivery platform, our mission is to deliver an amazing experience, fast, easy, and to your door. We operate in over 70+ countries worldwide, powered by tech, designed by people. As one of Europe’s largest tech platforms, 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. We enable creative minds to deliver solutions that create impact within our ecosystem. We move fast, take action and adapt. No matter where you're from or what you believe in, we build, we deliver, we lead. We are Delivery Hero.

Job Description

We are on the lookout for a Staff Data Scientist to join our Quick Commerce Commercial Tribe. In this role you will be exposed to various topics related to our Quick Commerce business – assortment optimisation, content generation, promotion effectiveness improvement, and ranking. You will help other Data Scientists to deliver high quality solutions, challenge our assumptions and improve DS practices across our teams.

As a Staff Data Scientist, you will work closely with multiple cross-functional teams (Data Scientists, Machine Learning Engineers, and Software Engineers) to build and maintain highly scalable and reliable ML services deployed in dozens of countries globally with millions of customers.

If you're a skilled Data Scientist and creative problem solver who is eager to deliver solutions and hungry for a new adventure, an international workplace is waiting for you in the heart of Berlin!

  • Guide the discovery of new innovative data products from conception to operationalization to help optimize our systems and improve the experience for our users.

  • Keep yourself up to date and suggest state-of-the-art models to find out what works best for our customers.

  • Be the main reference point for new research and tech quality of Data Science in Qcommerce Commercial & Media Solutions tribes.

  • Enable collaboration and knowledge sharing by pushing cross teams’ projects.

  • Set up our teams for success by creating a long-term vision, a mid-term strategy, and several short-term roadmaps toward some of the most complex and interesting data problems.

  • Last but not least, you are not afraid to build global systems that are used by thousands of people and constantly strive for excellence.

Qualifications

 

  • Sound statistical skills – you need to be very comfortable with fundamentals and first-principles thinking when it comes to statistics & machine learning theory.

  • Strong engineering fundamentals – you write maintainable code in Python that follows best practices in software engineering. You hold yourself and others to a high bar when working with production systems (observability, monitoring, performance).

  • Deep expertise in at least one relevant domain (e.g. causal inference, time series, Bayesian methods, neural networks, NLP/LLM, ranking/matching, advanced experimentation)

  • Before starting to work on a use case, you carefully question existing assumptions and care a lot about clean data.

  • You are a good communicator and are able to filter down requirements coming from many stakeholders to the ones that make an MVP.

  • You care about agile software processes, data-focused development, reliability, and disciplined experimentation.

  • You have experience mentoring other team members.

Nice to have:

  • Demonstrated leadership abilities in an engineering environment in driving operational excellence and best practices.

  • Experience in designing and implementing large scalable distributed systems with micro-services and heterogeneous platform components.

  • Knowledge of GCP. 

  • Proven records of knowledge sharing activities like presenting in conferences or publications. 

  • You know about A/B testing and are able to discern signals from noise when it comes to estimating the effect of new models.

Additional Information

Ensuring you and all our Heroes are looked after, happy, and healthy is always on the menu. Because if you’re in good shape, then we’re in good shape.

  • Make the most of our hybrid working model and join the team for face-to-face connection and collaboration in our beautiful Berlin campus 2 days a week

  • We offer 27 days holiday with an extra day on 2nd and 3rd year of service

  • We will support you in developing yourself and your career growth opportunities: 1.000 € Educational Budget, Language Courses, Parental Support and access to the Udemy Business platform to explore a variety of online courses.

  • Get moving and release those wonderful, mind-boosting endorphins: Health Checkups, Meditation, Yoga, Gym & Bicycle Subsidy

  • Cash. Dough. Cheddar. Whatever you call it, we’ll help you with it: Employee Share Purchase Plan, Sabbatical Bank,  Public Transportation Ticket Discount, Life & Accident Insurance, Corporate Pension Plan

  • The power of getting together over some food is unrivaled. Here are a few ways to help you do that. All the yum: Digital Meal Vouchers, Food Vouchers, Corporate Discounts and Courses.

Ready to join our team? If you’re excited to grow, collaborate and be part of the world’s leading delivery platform, we’d love to hear from you. Apply today!

We believe diversity and inclusion are key to creating not only an exciting product, but also an amazing customer and employee experience. Fostering this starts with hiring - therefore we do not discriminate on the basis of racial identities, religious beliefs, color, national origin, gender identities or expressions, sexual orientations, age, marital or disability statuses, or any other aspect that makes you, you. We encourage you to let us know if you need any accommodations or specific accessibility support to ensure a smooth interview experience—just include it in your application. You're welcome to share your pronouns (he/she/they) right from the start so we can address you respectfully from our first contact.

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CEO of Delivery Hero
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Niklas Östberg
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Average salary estimate

$100000 / YEARLY (est.)
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$80000K
$120000K

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What You Should Know About Staff Data Scientist - Quick Commerce, Delivery Hero

If you're a passionate and skilled Staff Data Scientist looking to make a significant impact, Delivery Hero in Berlin, Germany, is the place for you! As part of our Quick Commerce Commercial Tribe, you’ll immerse yourself in exciting challenges like assortment optimisation and promotion effectiveness, all while collaborating with talented Data Scientists, Machine Learning Engineers, and Software Engineers. Imagine being at the forefront of decision-making, guiding teams towards innovative data solutions that enhance the user experience in a fast-paced environment. Your role will not only involve improving existing practices but also discovering new, cutting-edge models that will optimize our systems on a global scale, impacting millions of customers worldwide. We value your creativity and analytical mindset, as you'll be challenged to question assumptions and ensure our data quality is top-notch. Plus, you'll get to mentor fellow team members, fostering a collaborative spirit that thrives on knowledge sharing. If you love creating robust ML services and are excited about a diverse, international work culture, we can’t wait to welcome you to our team at Delivery Hero. Let’s embark on this adventure together, right in the heart of Berlin!

Frequently Asked Questions (FAQs) for Staff Data Scientist - Quick Commerce Role at Delivery Hero
What are the primary responsibilities of a Staff Data Scientist at Delivery Hero?

As a Staff Data Scientist at Delivery Hero, you will work on critical aspects of our Quick Commerce business, such as assortment optimisation, content generation, and improving promotional effectiveness. Your responsibilities will include guiding teams to discover innovative data products, maintaining high-quality standards in methods and practices, and collaborating across various departments to ensure the delivery of scalable ML services that enhance the customer experience.

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What qualifications do I need to become a Staff Data Scientist at Delivery Hero?

To qualify for a Staff Data Scientist position at Delivery Hero, you should possess strong statistical skills and comfortable with machine learning theories. Proficiency in Python with a focus on software engineering best practices is essential. You will also need expertise in relevant domains like causal inference or neural networks, as well as excellent communication skills to filter down stakeholder requirements for effective project outcomes.

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How does Delivery Hero support the development of its Staff Data Scientists?

Delivery Hero is committed to the professional growth of its Staff Data Scientists. We provide an educational budget of €1,000, access to language courses, and a variety of online learning opportunities through platforms like Udemy Business. This ensures that our team members continuously develop their skills and stay up-to-date with industry trends.

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What does the workplace culture look like at Delivery Hero?

At Delivery Hero, we pride ourselves on a vibrant workplace culture known for its diversity and inclusiveness. The hybrid working model allows our Staff Data Scientists to connect with their teams in Berlin while balancing remote work. We also ensure that our employees’ well-being is a priority, offering health checkups, wellness programs, and ample holiday time to recharge.

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Are there opportunities for advancement for Staff Data Scientists at Delivery Hero?

Absolutely! At Delivery Hero, there is room for growth and advancement for our Staff Data Scientists. With our supportive environment and commitment to professional development, you'll have opportunities to lead cross-functional projects, mentor junior team members, and collaborate with various teams, all of which can lead to greater responsibilities and leadership roles in the future.

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Common Interview Questions for Staff Data Scientist - Quick Commerce
Can you explain a complex data science project you worked on and your role in it?

When answering this question, focus on the project’s goals, your specific contributions, and the impact of your work. Use metrics, if possible, to demonstrate the success of the project and how it ties into the broader business objectives.

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How do you approach a new data problem?

Describe your methodology for tackling new data challenges, including how you assess existing assumptions, clean and prepare data, and determine which analytical approaches might be most effective. Employ examples from past experiences for clarity.

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What statistical methods are you most comfortable with and why?

Share your proficiency in various statistical methods relevant to the Staff Data Scientist role, such as Bayesian methods, regression analysis, or A/B testing, while explaining how each method has been beneficial in your past work.

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How do you ensure the quality of the data you work with?

Discuss your strategies for data validation and cleaning. Emphasize your experience with rigorous quality checks and balancing data integrity while addressing potential biases in the datasets.

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Have you ever mentored others in data science, and how did you approach it?

Describe your mentoring philosophy and experience. Highlight specific methods used to share knowledge, provide feedback, and foster learning in others, emphasizing the collaborative culture in data science.

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What tools and technologies do you use for data analysis and model deployment?

Detail your experience with tools like Python, R, and SQL, as well as any relevant libraries for machine learning and data visualization. Discuss your familiarity with deployment technologies and frameworks.

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How do you stay current with industry trends and advances in data science?

Share your strategies for staying informed—whether through conferences, online courses, publications, or professional networking. Highlight how this continuous learning impacts your work positively.

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What experience do you have with A/B testing?

Talk about your experience with designing statistical experiments and interpreting the results. Mention how you discern meaningful insights from data noise to maximize effectiveness.

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Can you give an example of a time you faced a significant challenge during a project?

When addressing this question, outline the challenge, the steps you took to overcome it, and the lessons learned. Focus on resilience and problem-solving abilities that align with Delivery Hero's fast-paced environment.

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How do you prioritize tasks when you have multiple projects to manage?

Share your approach to task management, such as using project management tools or techniques like Agile methodologies. Emphasize your ability to balance competing priorities while delivering on time.

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Our mission is to deliver an amazing experience, fast, easy, and to your door.

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Full-time, hybrid
DATE POSTED
January 27, 2025

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