Personalized Recommendation Engineer
We are seeking a skilled Data Scientist with strong experience in building recommendation systems to join our team. You will play a critical role in designing and optimizing personalized experiences for millions of users by transforming raw data into insights and automated systems.
The ideal candidate will have hands-on experience building and deploying recommendation systems using collaborative filtering, content-based methods, or hybrid approaches. They should be proficient in Python and machine learning libraries, such as Scikit-learn, TensorFlow, PyTorch, and LightFM. Experience with data analysis tools like SQL, Pandas, and Jupyter is also required.
The successful candidate will work closely with engineers and product managers to integrate models into production. They will develop and monitor metrics for model performance and user engagement impact. A strong grasp of personalization techniques and user segmentation strategies is essential.
* Design, build, and deploy scalable recommendation engines using collaborative filtering, content-based methods, or hybrid approaches.
* Develop user profiling models using clickstream and behavioral data.
* Leverage AI-driven product tagging to enhance metadata quality and retrieval.
* Analyze macro and micro fashion trends to influence product rankings.
* Extract insights from large-scale user data and convert them into actionable models.
* Work closely with engineers and product managers to integrate models into production.
* Develop and monitor metrics for model performance and user engagement impact.