Job Title: Data Scientist and Recommender Engineer
This is a key role in our company, focusing on building and deploying scalable recommendation engines using various techniques.
About the Job
We are seeking an experienced data scientist with strong skills in building and optimizing personalized experiences for millions of users. The ideal candidate will have hands-on experience with data analysis tools, machine learning libraries, and large-scale data pipelines.
* Main Responsibilities:
* Design and develop scalable recommendation systems 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:
* Bachelor's or Master's degree in Computer Science or equivalent field.
* At least 3 years of professional experience in data science and machine learning.
* Hands-on experience with Python, machine learning libraries (e.g., Scikit-learn, TensorFlow), and data analysis tools (e.g., SQL, Pandas).
* 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.