Staff Data Scientist - Quick Commerce (all genders)

Berlin, Germany

Delivery Hero

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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, 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 looking for Staff Data Scientist (all genders) to join our "Quick Commerce Commercial & Media Solutions Tribes”. In this role you will be exposed to various topics related to our QCommerce business – assortment optimisation, content generation, price recommendation, promotion effectiveness improvement, and our internal AdTech solution. 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!

Your mission:

  • 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

  • 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

  • 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

  • Look up and go for it. We will support you in developing yourself and your career: 1.000 € Educational Budget, Language Courses, Parental Support

  • 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

At Delivery Hero, 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. Just be yourself and we can’t wait to see what value you bring to the role. We're as interested in your character as we are in your talent.

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* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰

Tags: A/B testing Agile Bayesian Causal inference Distributed Systems Engineering GCP LLMs Machine Learning MVP NLP Python Research Statistics Testing

Perks/benefits: Career development Conferences Flex vacation Insurance Yoga

Region: Europe
Country: Germany
Job stats:  8  1  0

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