We are seeking a skilled data scientist to 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 strong experience in building recommendation systems, developing user profiling models using clickstream and behavioral data, and leveraging AI-driven product tagging to enhance metadata quality and retrieval.
Key responsibilities include:
* Designing, building, and deploying scalable recommendation engines using collaborative filtering, content-based methods, or hybrid approaches.
* Developing user profiling models using clickstream and behavioral data.
* Leveraging AI-driven product tagging to enhance metadata quality and retrieval.
* Analyzing macro and micro fashion trends to influence product rankings.
* Extracting insights from large-scale user data and converting them into actionable models.
* Working closely with engineers and product managers to integrate models into production.
* Developing and monitoring metrics for model performance and user engagement impact.
The successful candidate will have the following qualifications:
* 2+ years of experience in data science, ideally in e-commerce or consumer-tech.
* Hands-on experience building and deploying recommendation systems (e.g., matrix factorization, deep learning-based recommenders, implicit/explicit feedback models).
* Proficiency in Python and machine learning libraries (e.g., Scikit-learn, TensorFlow, PyTorch, LightFM).
* Experience with data analysis tools such as SQL, Pandas, and Jupyter.
* Strong grasp of personalization techniques and user segmentation strategies.
* Solid understanding of product ranking using behavioral data and trend signals.
* Experience working with large-scale data pipelines and A/B testing frameworks.
* Strong communication and problem-solving skills.
Prior experience in the fashion or lifestyle e-commerce domain is preferred, as well as knowledge of modern MLops workflows and model monitoring tools. Background in NLP or computer vision for fashion tagging is also a plus.
This is an exciting opportunity for a data scientist to join our team and contribute to the development of cutting-edge AI technologies that transform how customers discover products.