About This Role
* We are seeking a skilled Data Scientist to join our growing team.
* The ideal candidate will have strong experience in building recommendation systems and transforming raw data into insights and automated systems.
Key Responsibilities:
1. Design, build, and deploy scalable recommendation engines using collaborative filtering, content-based methods, or hybrid approaches.
2. Develop user profiling models using clickstream and behavioral data.
3. Leverage AI-driven product tagging to enhance metadata quality and retrieval.
4. Analyze macro and micro fashion trends to influence product rankings.
5. Extract insights from large-scale user data and convert them into actionable models.
6. Work closely with engineers and product managers to integrate models into production.
7. Develop and monitor metrics for model performance and user engagement impact.
Required Skills and Qualifications:
* 2+ years of experience in data science, ideally in e-commerce or consumer-tech.
* Hands-on experience building and deploying recommendation systems (e.g., matrix factorization, deep learning-based recommenders, implicit/explicit feedback models).
* 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.
* 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.
Bonus 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.
We Value Diversity and Inclusion:
We welcome candidates from diverse backgrounds and experiences. If you're passionate about data science and eager to contribute to a fast-paced and innovative environment, we encourage you to apply.