Anzahl der Bewerber
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Do you want to use your passion and talent to make consumption more sustainable?
We're Europe's fastest-growing marketplace for refurbished products, empowering customers to acquire items up to 40% cheaper while making a substantial impact on reducing CO2 emissions compared to buying new devices.
Since our launch in February 2017, we grew to more than 300 employees and expanded across the European region. Throughout this journey, we've successfully concluded three substantial funding rounds, selling hundreds of thousands of products. Thanks to our team's efforts, we were recognized as the Top Employer in the DACH region (2023 and 2024) by Kununu and secured the title of an ACM Preferred Employer (2023).
As our new Senior Data Scientist - Pricing/Revenue Management, you will play a crucial role in transforming data into models that provide actionable insights and driving key decision-making processes. You will work on diverse projects, from data exploration and cleaning to building sophisticated machine learning models and visualising data insights. Your expertise will help us solve complex business problems and enhance our services.
What you'll do:
Who you are:
WHY YOU WILL ENJOY WORKING WITH US
Our Culture and Values:
Personal & Professional Development:
Flexibility:
…and much more! See for further insights!
Annual gross salary in euros for a full-time position
Where are you currently based (city, country)? *
Are you currently legally entitled to be employed on a full time contract in Europe? *
LinkedIn Profile
Do you have a Master's degree in Natural Sciences, Mathematics, Data Science or Computer Science? *
Do you have 5+ years of relevant experience in data science? *
Do you have experience working in an e-commerce company? *
Do you have 3-5 years experience with pricing/revenue management? *
Do you have strong coding skills in Python and SQL?
Do you have experience with both BigQuery and PostgreSQL?
Do you have experience with cloud computing? (Google Cloud is our preference)
Do you have a history of working with the standard data science stack: scikit-learn, PyTorch, pandas, matplotlib, Jupyter, etc. *
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