As a highly skilled Data Scientist with strong experience in building recommendation systems, 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.
About the Role
* You will 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
You will be responsible for:
* Designing and deploying recommendation systems that deliver personalized experiences for millions of users.
* Developing user profiling models that leverage clickstream and behavioral data.
* Enhancing metadata quality and retrieval using AI-driven product tagging.
* Analyzing macro and micro fashion trends to inform product rankings.
* Converting user data into actionable models that drive business results.
Requirements
To succeed in this role, you will need:
* At least 3 years of professional experience in data science, ideally in e-commerce or consumer-tech.
* Hands-on experience building and deploying recommendation systems.
* Proficiency in Python and machine learning libraries such as Scikit-learn, TensorFlow, PyTorch, LightFM.
* Experience with data analysis tools such as SQL, Pandas, and Jupyter.
* A strong grasp of personalization techniques and user segmentation strategies.
* A 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
We are looking for candidates with:
* Experience in the fashion or lifestyle e-commerce domain.
* Knowledge of modern MLops workflows and model monitoring tools.
* Familiarity with cloud platforms such as AWS or GCP and tools like Airflow or DBT.
* A background in NLP or computer vision for fashion tagging is a plus.