Data Scientist / ML Engineer

Nice-to-Have Skills

Experience with eCommerce Search.
Experience in Microservices, Event-Driven Architectures, and CI/CD Pipelines.
Background Check: Before Onboarding
Required Qualifications

Bachelor's degree in Computer Science, Engineering, Data Science, or a related quantitative field.
8 12 years of overall IT experience with 3+ years of hands-on experience in machine learning, data science, search relevance, or ranking systems.
Strong expertise in Python and ML frameworks such as MLFlow, TensorFlow, PyTorch, Scikit-learn, or equivalent.
Experience with statistical analysis, data exploration, and large-scale datasets.
Hands-on experience with Pandas, NumPy, Spark, feature engineering, and data preprocessing.
Experience building ranking models (Learning-to-Rank, Neural Ranking, or similar).
Experience with semantic search, embeddings, or dense retrieval methods.
Strong knowledge of Elasticsearch, Solr, OpenSearch, Lucene, BM25, information retrieval, search relevance tuning, tokenization, stemming, and query parsing.
Experience with MLOps, including model versioning, experiment tracking, and pipeline orchestration.
Strong SQL skills.
Excellent analytical, problem-solving, communication, and cross-functional collaboration skills.
Preferred Skills

Search query analysis and user behaviour analysis.
Training and fine-tuning machine learning models.
Experience with Large Language Models (LLMs) and prompt engineering.
Semantic indexing and dense vector search (Vector Databases).
Search metrics evaluation and optimization.
Tableau, Looker, or similar analytics tools.
Background in NLP, Information Retrieval, or Computational Linguistics.
Experience working on search or ML-focused teams.