Anunciada dia 13 junho
Descrição
Personalized Recommendation Systems Engineer
Transforming raw data into actionable insights and automated systems is a key responsibility of this role. By designing, building, and deploying scalable recommendation engines using collaborative filtering, content-based methods, or hybrid approaches, you will play a critical part in delivering personalized experiences for millions of users.
Key Responsibilities:
* Design and develop user profiling models using clickstream and behavioral data to create targeted recommendations.
* Leverage AI-driven product tagging to enhance metadata quality and retrieval, enabling more accurate product rankings.
* Analyze macro and micro fashion trends to influence product placements and drive user engagement.
* Extract insights from large-scale user data and convert them into actionable models that inform business decisions.
Required Skills and Qualifications:
* 2+ years of experience in data science, preferably in e-commerce or consumer-tech.
* Proficiency in Python and machine learning libraries, such as Scikit-learn, TensorFlow, PyTorch, and LightFM.
* Familiarity with data analysis tools, including 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.
This position requires a unique blend of technical expertise, business acumen, and creativity to drive innovation and growth.
We are looking for a highly skilled individual who can thrive in a fast-paced environment and make a significant impact on our organization.
