Applied Scientist - Wholesale Analytics

Recruiter
Zalando
Location
Berlin
Posted
25 Oct 2021
Closes
02 Jan 2022
Ref
3595300
Function
Wholesale
Level
Manager
At Zalando, our goal is to become the “Starting Point of Fashion” - we want our customers to always start their fashion journey from the Zalando shop, knowing that anything fashion-related could be easily found.

As the In-Season Management and Data Products team, we support this vision by ensuring relevant assortment is available to our customers and providing a great shopping experience. We want to achieve high product availability to minimise lost sales while controlling for overstock/underperformance to increase profitability.

As the Applied Scientist in our team, you'll be working with other Data Scientists and stakeholders to build the ML solutions that help Zalando place the right orders for the right articles at the right time.
WHERE YOUR EXPERTISE IS NEEDED
  • Analyze, experiment, evaluate and implement data science solutions focussed on high product and assortment availability. Have a hands-on mentality and love to solve complex problems with generating insights.
  • Translate business problems into project plans and solution designs using state of the art technology and methods.
  • Collaborate with technical teams within your department and with business stakeholders across the company to bring the developed models in production.
  • Drive data analytics and data science products within the team and your department. Actively exchange with other data scientists, analysts, engineers and commercial colleagues to untap new sources of data and know-how.
  • Commercially minded attitude: build fit-for-purpose solutions that directly deliver business results with high impact.
  • Fostering an inclusive and diverse team environment.

WHAT WE ARE LOOKING FOR
  • You have 4+ years hands-on experience in applied/data sciences, and have industry or consulting experience through-out the data science cycle from data preparation/feature engineering to go-live of a model. Masters level or higher degree in a quantitative field is preferred (e.g. in Data Science, Computer Science, Statistics, Econometrics)
  • Advanced skills in Python and libraries related to data science such as pandas, scikit-learn, Keras. Strong experience with SQL is necessary. Experience with big data technologies such as Spark are a plus. Curious about learning new technologies.
  • Hands-on experience in developing and deploying machine learning algorithms used in business applications.
  • Strong communicator to challenge the status quo, tell data stories, maximize decision impact of your results and liaison with commercial and tech people alike.
  • Proactive, fast learner, problem solver, comfortable working in English in a fast paced international work environment.

PERKS AT WORK
  • Culture of trust, empowerment and constructive feedback, open source commitment, meetups, game nights, 70+ internal technical and fun guilds, knowledge sharing through tech talks, internal tech academy and blogs, product demos, parties & events
  • Competitive salary, employee share shop, 40% Zalando shopping discount, discounts from external partners, centrally located offices, public transport discounts, municipality services, great IT equipment, flexible working times, additional holidays and volunteering time off, free beverages and fruits, diverse sports and health offerings
  • Extensive onboarding, mentoring and personal development opportunities and an international team of experts
  • Relocation assistance for internationals, PME family service and parent & child rooms* (*available in select locations)

We celebrate diversity and are committed to building teams that represent a variety of backgrounds, perspectives and skills. All employment is decided on the basis of qualifications, merit and business need.

Zalando SE

Zalando is Europe’s leading online platform for fashion and lifestyle, connecting customers, brands and partners across 17 markets. We drive digital solutions for fashion, logistics, advertising and research, bringing head-to-toe fashion to more than 35+ million active customers through diverse skill-sets, interests and languages our teams choose to use.

Please note that all the applications must be completed using the online form - we do not accept applications via e-mail.

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