Data Scientist

Thompsons Hr Consulting; Bengaluru; On-site; INR 1,200,000 - 1,800,000; Full time

Job summary

Thompsons Hr Consulting is looking for a hands-on Data Scientist specializing in NLP to design, build, evaluate, and deploy production-grade NLP and ML solutions for complex text-driven workflows.

You will design NLP/ML pipelines for unstructured data, develop retrieval systems for semantic search and ranking, and collaborate with platform and product teams to deploy reliable ML services across the organization.

Qualifications

• Experience building production-grade NLP pipelines.
• Experience with text classification, semantic similarity, embeddings, retrieval.
• Familiar with evaluating models and experiments.
• Experience communicating findings to technical and non-technical stakeholders.

Responsibilities

• Design and build NLP/ML pipelines from noisy text.
• Develop semantic search and ranking systems using embeddings.
• Evaluate supervised and hybrid approaches including NER, clustering.
• Analyze decision boundaries and feature relationships.
• Deploy and monitor ML services with cross-functional teams.

Skills

Python

SQL

NLP

Production pipelines

Information retrieval

Tools

Hugging Face

SentenceTransformers

Tokenization

Transformer models

Model evaluation

Job description

Role & responsibilities

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.