Senior Applied Scientist - Retail Forecast (all genders)

Key Skills

Data science techniques, Gurobi, Machine learning techniques, Optimization, Python Programming

Job Description

THE ROLE & THE TEAM

Have you ever experienced the pain that you have to wait extra weeks for your favourite shoes to become available again? Do you want to help Zalando ease the pain of our customers? Come join us! We are a team of applied scientists and engineers aiming to provide a flawless shopping experience by providing accurate demand forecasts for our customers, and to achieve unit economics by smart stock management. As the Senior Applied Scientist in demand forecast, you'll be working with other Data Scientists and stakeholders to build the next-gen forecast models to support stock planning decisions.

WHAT WE’D LOVE YOU TO DO (AND LOVE DOING)

• Actively contribute to the team roadmap, and work closely with product managers and engineers to identify areas of opportunity and resource requirements to deliver impactful projects
• Conceptualize, prototype, and productionize state-of-the-art demand forecast solutions. You enjoy finding solutions to new complex problems and don’t mind getting your hands dirty (with pen and paper or in your IDE of choice).
• Communicate technical problems and results effectively with other team members and also with (less technical) stakeholders. Educate them about your products and solutions.
• Be the owner of the whole development cycle of algorithms - from opportunity discovery to production. Iteratively improve models and explore the art of possibility (e.g. new data sources, new ways of structuring the problem)
• Build model pipelines and streamline analysis processes, using common programming tools (e.g. Python, R, Scala, SQL, PyTorch, Tensorflow etc.)

WE'D LOVE TO MEET YOU IF

• Master degree or above (PhD) in quantitative economics, statistics, mathematics, physics, operation research or a related quantitative discipline with a strong theoretical foundation in statistics, econometrics, time series analysis, and machine learning methodologies. Command of causal inference is a big plus
• At least 5 years of industry experience (3 years with PhD degree) in developing forecasting models, using both statistical methods and machine learning techniques. Understand the tradeoff of each method and their areas of applications. Have deep knowledge of the state of the art practices in forecasting, but also maintain a bias for simplicity
• Extensive experience with Python and its associated data science libraries, including writing production quality code (not just notebooks). Familiarity with optimization software such as Gurobi a plus.
• Excellent verbal and written communication skills with a curious and self-starter mindset. Ability to unblock yourself, but also proactively request support when needed to remove roadblocks

If you think you have what it takes, we encourage you to apply even if you don't meet every single requirement. You may just be the right candidate for this or other roles!

INCLUSIVE BY DESIGN

At Zalando, our vision is to be inclusive by design. And this vision starts with our hiring - we do not discriminate on the basis of gender identity, sexual orientation, personal expression, ethnicity, religious belief, or disability status. You are welcome to leave out your picture, age, or marital status from your application. We only assess candidates on their qualifications and merit.

We want to provide you with a great candidate experience. Feel free to inform us of any accommodations you may need, so we can best support you throughout the hiring process.

OUR OFFER

Zalando provides a range of benefits, here’s an overview of what you can expect. Ask your Talent Acquisition Partner to learn more about what we offer.

• Employee shares program
• 40% off fashion and beauty products sold and shipped by Zalando, 30% off Zalando Lounge, discounts from external partners
• 2 paid volunteering days a year
• Hybrid working model with 60% (or more) remote per week, actual practice is up to each team to best support their collaboration
• Work from abroad for up to 30 working days a year
• 27 days of vacation a year to start
• Relocation assistance available (subject to prior agreement)
• Family services, including counseling and support
• Health and wellbeing options (including Gympass)
• Mental health support and coaching available
• Drive your development through our training platform and biannual peer-to-peer review