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Job Description
**WHO WE ARE**
LuxExperience is the leading digital, multi-brand luxury group and the online shopping destination for luxury enthusiasts worldwide.
LuxExperience operates a portfolio of some of the most distinguished store brands in digital luxury and creates communities for luxury enthusiasts with unique digital and physical experiences.
Mytheresa, NET-A-PORTER and MR PORTER offer highly curated edits of the most prestigious luxury brands across the world, featuring womenswear, menswear, kidswear, fine jewelry & watches, and lifestyle products.
YOOX and THE OUTNET are the leading destinations for multi-brand off-season online luxury shopping.
The NYSE-listed group operates in key markets worldwide. For more information, please visit [https://investors.luxexperience.com](https://investors.luxexperience.com/).
LuxExperience is now seeking a talented **Data Scientist** to join the Team.
**WHAT YOU WILL DO**
- As a Data Scientist at LuxExperience Group, you will be working with commercial and marketing business stakeholders to provide smart data automations and support their decision-making.
- Train, deploy and monitor machine learning, recommendation and Generative AI models in production.
- Work alongside software developers in building applications to service your data and models
- Build production-grade code
- Work with stakeholders throughout the business to encourage a data-driven approach through the delivery of automated data products and accessible, actionable insight.
- Identify opportunities to improve the efficiency of the Data Science team through improved work practices and the development of data assets.
**WHO YOU ARE**
- Bachelor’s or Master’s degree in Math, Statistics, Computer Science or similar
- 4+ years of professional experience (at least 5+ models in production delivering consistent business value)
- Working knowledge of Databricks & MLflow, LLM frameworks (e.g., LangChain or LlamaIndex), and Vector databases and embedding models
- Expert level in Python, SQL, and working knowledge of PySpark, GIT & CICD and Object-Oriented Programming
- Experienced with Atlassian suite (Jira, Bitbucket, and Confluence) and PyCharm or Visual Studio
- Strong foundation in key topics of statistics, including sample selection, probability, hypothesis testing, and linear regression.
- Strong understanding of key machine learning algorithms, including logistic regression, decision trees, random forests, and clustering algorithms.
**WHAT WE OFFER**
- 30% staff discount on http://mytheresa.com
- Discounted travel card (public transportation)
- Gym membership discount
- Fresh fruit every afternoon and coffee flat-rate
- Discounted lunch options
- Pension contributions in Germany
- 28 days of holiday p.a.
- Mobile office with up to 20% of your total contracted hours (job and position permitting)
- Corporate benefits platform
- E-learning platform/language classes
- 10 days/year of mobile office abroad in EU countries (job and position permitting)
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### *LuxExperience is an equal opportunities employer, we encourage people with a diverse range of backgrounds to apply. We recognize and celebrate the benefits that diversity brings to our workplace, our business and our customers. We welcome and will consider all applications regardless of race and nationality, religion, color, sex, pregnancy or related medical conditions, parental status, sexual orientation, gender identity, gender expression, age, status as an individual with a disability, or any other legally protected characteristics.*
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### *If you require any reasonable adjustments to complete your application, please do not hesitate to advise us accordingly.*
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Experience Level: Mid-Senior levelWorkplace Type: Hybrid
Key Responsibilities
Collaborate with commercial and marketing stakeholders to provide smart data automations and support decision-making.
Train, deploy, and monitor machine learning, recommendation, and Generative AI models in production.
Build production-grade code and work alongside software developers to service data and models.
Encourage a data-driven approach through the delivery of automated data products and actionable insights.
Identify opportunities to improve Data Science team efficiency through improved work practices and data asset development.