CDIBengaluru, India
Data Scientist AI
Hybride
We are looking for a hands-on Data Scientist specializing in Natural Language Processing to design, build, evaluate, and deploy production-grade NLP and machine-learning solutions for complex text-driven workflows. Core Responsibilities • Design and build NLP and machine-learning pipelines that transform noisy, heterogeneous text data into clean semantic layers ready for modeling, retrieval, analytics, and downstream product use. • Develop retrieval systems for semantic search, candidate ranking, out-of-vocabulary handling, and high-quality information discovery using embeddings and vector search. • Build, compare, and evaluate supervised and hybrid approaches, including multioutput classifiers, hierarchical classifiers, NER-style parsers, clustering techniques, and rule-plus-ML systems. • Analyze decision boundaries and relationships across free-text fields using conditional distributions, entropy, mutual information, directional association, embeddings, and predictive ablation studies. • Deploy, monitor, and continuously improve ML services in collaboration with platform, backend, data engineering, and product teams. Required Skills • Strong Python and SQL skills, with hands-on experience building production data pipelines and machine-learning workflows. • Practical experience with text classification, semantic similarity, embeddings, information retrieval, ranking, clustering, or entity extraction. • Experience with Hugging Face, SentenceTransformers, tokenization, fine-tuning, transformer-based models, and model evaluation. • Solid understanding of vector search, cosine similarity, approximate nearest-neighbor methods, and retrieval metrics such as Recall@K, MRR, and NDCG. • Ability to design experiments, define evaluation metrics, compare model trade-offs, and communicate findings clearly to technical and non-technical stakeholders.
Nice to Haves • Experience with healthcare, imaging, enterprise metadata, document intelligence, search, recommendation, knowledge retrieval, or routing systems. • Knowledge of DICOM, PACS/RIS, HL7/FHIR, or other structured-plus-free-text enterprise data standards. • Familiarity with MLOps, cloud deployment, API-based model serving, monitoring, responsible AI practices, or privacy-aware handling of sensitive text data.
Informations de la mission :
Nice to Haves • Experience with healthcare, imaging, enterprise metadata, document intelligence, search, recommendation, knowledge retrieval, or routing systems. • Knowledge of DICOM, PACS/RIS, HL7/FHIR, or other structured-plus-free-text enterprise data standards. • Familiarity with MLOps, cloud deployment, API-based model serving, monitoring, responsible AI practices, or privacy-aware handling of sensitive text data.
Informations de la mission :
- Début de mission : 26/07/2026
- Durée : 6 mois
- Date de publication : 15/07/2026
- Date limite de candidature : 31/10/2026
Compétences recherchées
Python (Indispensable)SQL (Indispensable)Hugging Face (Indispensable)SentenceTransformers (Indispensable)tokenization (Indispensable)fine-tuning (Indispensable)transformer-based models (Indispensable)embeddings (Indispensable)vector search (Indispensable)cosine similarity (Indispensable)approximate nearest-neighbor (Indispensable)Recall@K (Indispensable)MRR (Indispensable)NDCG (Indispensable)DICOM (Indispensable)PACS/RIS (Indispensable)HL7/FHIR (Indispensable)MLOps (Indispensable)cloud deployment (Indispensable)API-based model serving (Indispensable)monitoring (Indispensable)NLP (Indispensable)Text classification (Indispensable)Semantic similarity (Indispensable)Embeddings (Indispensable)Information retrieval (Indispensable)Ranking (Indispensable)Clustering (Indispensable)Entity extraction (Indispensable)Tokenization (Indispensable)Fine-tuning (Indispensable)Transformer-based models (Indispensable)Model evaluation (Indispensable)Vector search (Indispensable)Cosine similarity (Indispensable)Approximate nearest-neighbor (Indispensable)Retrieval metrics (Recall@K (Apprécié)NDCG) (Indispensable)Cloud deployment (Indispensable)
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