Data Scientist for Personalization
Há 5 dias
FARFETCH Group exists to revolutionize the global luxury fashion industry. Our mission is to connect creators, curators, and consumers through cutting-edge technology. We're a positive force for good, bringing together a diverse community of people, partners, and customers who share our passion for innovation and excellence.
**Technology at the Heart**
We operate a modular end-to-end technology platform purpose-built to power the luxury fashion ecosystem worldwide. Our team of experts works tirelessly to address complex challenges and drive growth. We empower each other to break traditions and push boundaries, with the freedom and autonomy to make a meaningful impact on our customers' lives.
**About the Role**
We're seeking an exceptional Data Scientist to join our team in building an advanced personalization platform for online services. You'll work closely with software engineers, data scientists, and machine learning engineers to design and implement state-of-the-art models for search, recommendations, and hyper-personalization. Your expertise will be instrumental in driving business growth and improving customer experience.
**Key Responsibilities**
1. Collaborate with technical partners to develop end-to-end architecture solutions;
2. Design model serving solutions and develop machine learning-based applications, services, and APIs to productionize machine learning models;
3. Partner with data scientists and software engineers to provide an end-to-end solution for machine learning-based projects;
4. Continuously optimize machine learning models and pipelines to improve performance and efficiency;
5. Foster technological evolution and improve quality attributes of services.
**Requirements**
1. Bachelor's degree in Computer Science, Machine Learning, Data Science, or related fields;
2. Experience implementing end-to-end data products with data engineering and machine learning components;
3. Proficiency in writing production-quality code in Python, including dependency management and testing frameworks;
4. Familiarity with popular machine learning practices, libraries, and platforms (e.g., MLflow, Databricks, Spark, MLlib, PyTorch, Numpy, Pandas, TensorFlow, Scikit-learn);
5. Experience with Continuous Integration & Continuous Deployment processes and platforms, software design patterns, and APIs;
6. Knowledge of Kubernetes;
**What We Offer**
$115,000 - $145,000 per year, depending on experience; a dynamic work environment; opportunities for growth and development; and a chance to work on challenging projects that drive business success.
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