Key Responsibilities:
* Develop and deploy scalable recommendation engines using collaborative filtering, content-based methods, or hybrid approaches.
* Create 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.
Required Skills and Qualifications:
* A strong background in data science, preferably in e-commerce or consumer-tech.
* Hands-on experience building and deploying recommendation systems.
* Proficiency in Python and machine learning libraries.
* Experience with data analysis tools such as SQL, Pandas, and Jupyter.
* A solid understanding of personalization techniques and user segmentation strategies.
* Strong communication and problem-solving skills.
About the Role:
This role requires a skilled Data Scientist with expertise in building recommendation systems to join our growing 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.
Preferred Qualifications:
* Experience in the fashion or lifestyle e-commerce domain.
* Familiarity with cloud platforms and tools like Airflow or DBT.
* Background in NLP or computer vision for fashion tagging is a plus.