Data Scientist - Personalization Engineer
Transforming Customer Experiences through Data-Driven Insights
We are seeking a skilled Data Scientist with strong experience in building recommendation systems to join our team.
* 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 Requirements:
To be successful in this role, you will need:
* A minimum of 3 years of professional Python & ML experience.
* A Master's Degree in Computer Science or Equivalent.
* Hands-on experience building and deploying recommendation systems.
* 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.
* 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.
* Strong communication and problem-solving skills.
The ideal candidate will have experience in the fashion or lifestyle e-commerce domain and knowledge of modern MLops workflows and model monitoring tools. Familiarity with cloud platforms (AWS, GCP) and tools like Airflow or DBT is also preferred. Background in NLP or computer vision for fashion tagging is a plus.