Data Scientist - Fashion Insights Engineer
We are seeking a skilled Data Scientist with strong experience in building recommendation systems to drive personalized experiences for millions of users.
Key Responsibilities:
* 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.
Required Skills and 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.
Preferred Qualifications:
* Experience in the fashion or lifestyle e-commerce domain.
* Knowledge of modern MLops workflows and model monitoring tools.
* Familiarity with cloud platforms (AWS, GCP) and tools like Airflow or DBT.
* Background in NLP or computer vision for fashion tagging is a plus.