Key skills
PythonMachine LearningPyTorchTensorFlowscikit-learnXGBoostMilvusSparkHadoopElasticsearchSolr
About this role
Job Description:
Elasticsearch and Learn to Rank expertise -
Job Description:
We are seeking a highly skilled Data Scientist with a strong background in e-commerce search technologies to join our team on an immediate basis. The ideal candidate will have experience working with Learn to Rank (LTR) models, vector search, and retrieval algorithms to drive relevance and performance in large-scale search systems.
Required Skills & Experience:
- Proven experience in e-commerce or similar domains focused on search and ranking.
- Strong expertise in Learn to Rank, vector similarity search, and retrieval models.
- Python and libraries such as scikit-learn, XGBoost, TensorFlow, or PyTorch.
- Experience with search engines (e.g., Elasticsearch, Solr, Vespa) and ANN frameworks (e.g., Faiss, Annoy, Milvus).
- Solid understanding of information retrieval concepts, relevance metrics, and evaluation methods.
- Familiarity with large-scale data processing (e.g., Spark, Hadoop) is a plus.
Key Responsibilities:
- Design, develop, and implement search ranking models using Learn to Rank approaches.
- Apply vector search techniques to improve relevance and personalization in search results.
- Develop scalable data pipelines to support retrieval algorithms and feature engineering.
- Collaborate with engineering, product, and UX teams to improve search experience.
- Analyze large-scale behavioral and clickstream data to inform algorithmic decisions.
- Rapidly prototype and iterate on models with measurable business impact.
Preferred Qualifications:
- Master's or PhD in Computer Science, Machine Learning, Data Science, or a related field.
- Experience working in fast-paced environments with quick turnaround timelines.