Job Title: Advanced Analytics Engineer - Fashion Technology
About the Role:
We are seeking an experienced Data Scientist to join our team and design, build, and deploy scalable recommendation engines using collaborative filtering, content-based methods, or hybrid approaches. As a key member of our analytics team, you will play a critical role in transforming raw data into actionable insights and automated systems that deliver personalized shopping experiences for millions of users.
Key Responsibilities:
* Recommendation Engine Development: Design, build, and deploy scalable recommendation engines that suggest relevant products to customers based on their browsing and purchasing behavior.
* User Profiling: Develop user profiling models using clickstream and behavioral data to better understand customer preferences and interests.
* AI-Driven Product Tagging: Leverage AI-driven product tagging to enhance metadata quality and retrieval, making it easier for customers to find what they're looking for.
* Fashion Trend Analysis: Analyze macro and micro fashion trends to influence product rankings and ensure that our customers see the most relevant and up-to-date products.
* Data Analysis and Insights: Extract insights from large-scale user data and convert them into actionable models that drive business decisions.
* Model Integration and Monitoring: Work closely with engineers and product managers to integrate models into production, monitor their performance, and optimize for maximum impact.
Requirements:
* Professional Experience: 2+ years of experience in data science, ideally in e-commerce or consumer-tech.
* Technical Skills: Hands-on experience building and deploying recommendation systems, proficiency in Python and machine learning libraries (e.g., Scikit-learn, TensorFlow, PyTorch, LightFM), and experience with data analysis tools such as SQL, Pandas, and Jupyter.
* Personalization Techniques: Strong grasp of personalization techniques and user segmentation strategies.
* Product Ranking: Solid understanding of product ranking using behavioral data and trend signals.
* Cloud Platforms and Tools: Experience working with large-scale data pipelines and A/B testing frameworks, and familiarity with cloud platforms (AWS, GCP) and tools like Airflow or DBT.
Preferred Qualifications:
* Fashion E-commerce Domain: Experience in the fashion or lifestyle e-commerce domain.
* MLops Workflows and Model Monitoring Tools: Knowledge of modern MLops workflows and model monitoring tools.
* NLP or Computer Vision: Background in NLP or computer vision for fashion tagging is a plus.