Zalando

Senior Applied Scientist - Demand Forecast

Zalando

Berlin, Germany · Full Time

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Experience
5+ yrs
Salary
—
Openings
1
Posted
1 day ago
Work mode
In office
Education
Master's degree or higher in quantitative disciplines
Resume
Required to apply

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Job description

About the Role and Team

The Partner Tech Applied Science team drives Zalando's growth by collaborating with Zalando Partners and internal stakeholders to enhance business outcomes. They develop products that deliver improved demand signals to partners, utilizing advanced technologies to keep the assortment relevant while safeguarding customer privacy.

As a Senior Applied Scientist, you will work in close partnership with product managers, engineers, and analysts to enhance a top-tier article demand forecast engine. You will co-lead the scientific roadmap for forecasting, collaborating with Principal Scientists and leaders to optimize forecast effectiveness by moving beyond traditional metrics towards genuine incremental improvements.

Key Responsibilities

  • Design, prototype, and deploy innovative demand forecasting models and solutions, tackling novel and complex challenges practically and creatively.
  • Effectively communicate technical issues and outcomes to both technical teams and non-technical stakeholders, educating them on your solutions and products.
  • Own the complete algorithm development lifecycle, from identifying opportunities through to production deployment, continuously improving models and exploring new possibilities such as novel data sources or problem structuring techniques.
  • Develop model pipelines and improve analysis workflows using tools like Python, R, Scala, SQL, PyTorch, and TensorFlow.
  • Mentor junior scientists and promote a culture of ongoing learning and knowledge sharing within the team.

Qualifications & Experience

  • Master's degree or higher in statistics, mathematics, physics, operations research, or related quantitative fields, with a solid theoretical background in statistics, time series analysis, and machine learning forecasting techniques.
  • Over 5 years of professional experience (at least 3 years for PhD holders) in developing forecasting models using both statistical and machine learning methods, with an understanding of their trade-offs and applicable use cases. Familiarity with state-of-the-art forecasting practices balanced with a preference for simplicity.
  • Strong verbal and written communication skills coupled with a proactive, self-starting approach. Ability to independently resolve obstacles as well as seek assistance to remove blockers.
  • Expertise in Python, SQL, and PySpark, adhering to high coding standards, including participating actively in code reviews and elevating team engineering practices.
  • Leadership experience guiding junior team members is preferred.

Benefits Offered

  • 27 days of paid holiday annually for full-time employees, increasing by one day per year up to a maximum of 30 days.
  • Discounts including 40% off Zalando fashion and beauty products, 30% off Lounge by Zalando, and deals with external partners.
  • Family support services, including counseling and dedicated assistance for parents and caregivers.
  • Company pension scheme and employee share programs.
  • Health and wellbeing initiatives including access to Wellhub, mental health support, and coaching.
  • Professional development via training platforms and biannual peer reviews.
  • Two paid volunteering days annually.
  • Relocation support subject to prior agreement.

Inclusion and Diversity

Zalando values diversity and fosters an inclusive environment where all backgrounds are welcomed. They minimize bias in hiring by focusing solely on skills, qualifications, and contributions, encouraging candidates to exclude personal details such as photos or marital status from applications. Accommodations during the recruitment process are available upon request to ensure accessibility for all candidates.

Minimum education

Master's Degree

How they work

Communication Teamwork & Collaboration Problem Solving Leadership Initiative

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