Senior Applied Scientist - Demand Forecast (all genders)

Posted Yesterday
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Berlin, DEU
In-Office
Senior level
eCommerce • Retail
The Role
Lead design, development, and productionization of demand forecasting models. Collaborate with product, engineering, and analytics teams to improve forecast performance, build model pipelines, mentor junior scientists, and communicate results to technical and non-technical stakeholders.
Summary Generated by Built In
THE ROLE & THE TEAM

The Partner Tech Applied Science team acts as the engine behind Zalando’s growth, partnering with Zalando Partners as well as internal stakeholders to achieve better business performance. We build products that provide better demand signals to partners. By leveraging cutting-edge technology, we ensure our assortment is relevant, engaging, and deeply respectful of customer privacy.
 

As a Senior Applied Scientist, you will collaborate closely with product managers, engineers, and analysts to refine our industry-leading article demand forecast engine. You will co-own the scientific roadmap for our forecast domain, working with Principal Scientists and leaders to maximize forecast performance by moving beyond simple metrics to true incrementally.
 

INCLUSIVE BY DESIGN
 

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! At Zalando, our vision is to be the leading pan-European ecosystem for fashion and lifestyle e-commerce – one that thrives on diversity and is truly inclusive by design. We believe that diverse teams fuel innovation and creativity, and we actively seek out talent from all backgrounds.
 

We actively seek to reduce bias in our hiring and employment processes, focusing on your qualifications, skills, and contributions. To support this, we kindly ask that you refrain from including personal details such as your photo, age, or marital status in your CV, ensuring a fair and equitable evaluation based solely on your abilities and potential.
 

We are committed to providing an exceptional and accessible candidate experience for everyone. If you require any accommodations to support you throughout the hiring process, please let us know – we are here to assist you.

Discover more about our commitment to creating a diverse and inclusive workplace: https://jobs.zalando.com/en/our-culture/diversity-and-inclusion
 

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

  • Mentor junior scientists and foster a culture of continuous learning and knowledge sharing within the team.          


WE’D LOVE TO MEET YOU IF…
 
  • (Required) PhD in statistics, mathematics, physics, operation research or a related quantitative discipline with a strong theoretical foundation in statistics, time series analysis, and machine learning methodologies related to forecasting.

  • (Required) At least 3 years of industry working experience 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

  • (Required) 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

  • (Required) Deep proficiency in Python, SQL, and PySpark, with a commitment to high coding standards, including active participation in code reviews and elevating the team's engineering culture.

  • (Preferred) Demonstrated leadership experience in guiding less experienced colleagues in their work

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.
 

  • 27 days of holiday a year to start for full-time employees (+1 day for every calendar year up to 30 days)

  • 2 paid volunteering days a year

  • Employee shares programme

  • 40% off fashion and beauty products sold and shipped by Zalando, 30% off Lounge by Zalando, discounts from external partners

  • Relocation assistance available (subject to prior agreement)

  • Family services, including counselling and support

  • Health and wellbeing options (including Wellhub, formerly Gympass)

  • Mental health support and coaching available

  • Drive your development through our training platform and biannual peer-to-peer review
     

Skills Required

  • PhD in statistics, mathematics, physics, operation research or a related quantitative discipline
  • Strong theoretical foundation in statistics, time series analysis, and machine learning methodologies related to forecasting
  • At least 3 years of industry experience developing forecasting models using statistical and machine learning techniques
  • Deep proficiency in Python, SQL, and PySpark with commitment to high coding standards and code reviews
  • Excellent verbal and written communication skills; curious, self-starter mindset
  • Experience productionizing models and building model pipelines (MLops/production experience)
  • Familiarity with PyTorch, TensorFlow, R, Scala
  • Demonstrated leadership experience guiding less experienced colleagues

Zalando Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Zalando and has not been reviewed or approved by Zalando.

  • Leave & Time Off Breadth Paid time off includes a sizable annual allowance that can grow with tenure, plus additional paid days for volunteering. This breadth is highlighted as supportive of work–life balance.
  • Wellbeing & Lifestyle Benefits Mental health support, round‑the‑clock counseling for employees and households, and broad fitness/wellness access are emphasized as robust. Substantial product discounts and partner offers add meaningful lifestyle value.
  • Parental & Family Support Structured support around parental leave—such as buddy programs, re‑onboarding, and paid child sick days—helps ease family responsibilities. Flexible and part‑time leadership options further accommodate parents.

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The Company
HQ: Berlin
10,000 Employees
Year Founded: 2008

What We Do

Welcome to Zalando. Here’s some key info about us: Our position and vision: - We’re Europe’s leading online platform for fashion and lifestyle - Founded in Berlin in 2008, we bring head-to-toe fashion to more than 50 million active customers in 25 markets; offering clothes, footwear, accessories, and beauty - Our vision is to become The Starting Point For Fashion. Our offering: - Our assortment of international brands ranges from world-famous names to local labels - Our platform is a one-stop fashion destination for inspiration, innovation, and interaction - As Europe’s most fashionable tech company, we work hard to find digital solutions for every aspect of the fashion journey: for our customers, partners, and friends of our brand. - Our logistics network with 12 centrally located fulfillment centers allows us to efficiently serve our customers throughout Europe, supported by warehouses in Italy, France, Poland, and Sweden with a focus on local customer needs. Our beliefs: - Our ambition is to combine our passion for self-expression through fashion with our unwavering commitments to sustainability and D&I - We believe that our integration of fashion, operations, and online technology gives us the capability to deliver a compelling value proposition to both our customers and fashion brand partners.

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