Data Scientist - Recommendation Systems Engineer
Job Description
We are seeking a skilled Data Scientist with strong experience in building recommendation systems to design and optimize personalized experiences for millions of users by transforming raw data into insights and automated systems.
About the Role
* 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.
Key Responsibilities
This role requires a strong understanding of personalization techniques and user segmentation strategies, as well as solid experience working with large-scale data pipelines and A/B testing frameworks. The ideal candidate will have hands-on experience building and deploying recommendation systems, proficiency in Python and machine learning libraries, and a strong grasp of product ranking using behavioral data and trend signals.
Requirements
* 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.
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.