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Data Scientist
Data ScientistETENICO RECRUITS • Bangalore
Data Scientist

Data Scientist

ETENICO RECRUITS • Bangalore
30+ days ago
Job description

Description : Data Scientist - Generative & Agentic AI (Healthcare Domain).

Educational Qualification : ME / BE / MCA.

Experience Required : 3-5 Years.

Shifts : Day Shift.

Mode : Hybrid.

Skills & Responsibilities :

Experience :

3+ years of experience in Machine Learning, Deep Learning, or Generative AI, with a strong focus on healthcare software product development and medical coding automation.

Programming & Frameworks :

  • Proficient in Python, with hands-on experience using Pandas, NumPy, and OOPs concepts.
  • Practical experience with PyTorch, TensorFlow, Keras, and Hugging Face Transformers.
  • Familiar with writing optimized SQL queries for large-scale structured clinical data.

Healthcare-Specific AI :

  • Strong understanding of medical coding standards (ICD, CPT, SNOMED), EHR systems, and clinical document processing.
  • Exposure to HL7, FHIR APIs, and privacy regulations like HIPAA is an added advantage.

    • Generative AI & NLP :

  • Experience working with LLMs, GANs, VAEs, and Diffusion Models in healthcare use cases (e.g., clinical summarization, automated coding, documentation assistance).
  • Familiar with Azure OpenAI, AWS Bedrock, DALLE, and Stable Diffusion platforms.
  • Strong grasp of NLP techniques such as Named Entity Recognition (NER), token classification, contextual embeddings, and deep learning models like RNN,
  • LSTM, GRU.

    • Agentic AI & Autonomous Workflows :

  • Experience or familiarity with building agentic systems using LangChain, AutoGen, or CrewAI for orchestrating multi-step tasks (e.g., claim validation, document parsing).
  • Ability to integrate autonomous agents with tool-based systems and APIs to enhance workflow efficiency.

    • Machine Learning & Statistical Modeling :

  • Expertise in supervised and unsupervised ML, including Random Forest, SVM, Boosting, Bagging, Regression, and Clustering methods.
  • Strong capability in feature engineering, model training, and cross-validation for healthcare data.

    • MLOps, Deployment & Data Integration :

  • Experience with cloud platforms such as AWS, Azure, or GCP for scalable ML model deployment.
  • Familiarity with MLOps practices, CI / CD pipelines, Docker, Kubernetes, and model versioning.
  • Hands-on experience with Apache NiFi for data ingestion, integration, and workflow automation, including designing NiFi flows for structured / unstructured clinical data and seamless integration with downstream ML models.
  • Proficient with Linux systems and GPU-based ML workflows.

    • Research, Compliance & Ethics :

  • Experience contributing to AI research, open-source projects, or Kaggle competitions focused on healthcare or NLP.
  • Awareness of AI ethics, bias mitigation, explainability techniques, and safe deployment of AI in clinical settings.

    • Soft Skills & Collaboration :

  • Proven ability to work independently and in agile teams with product managers, clinical SMEs, and backend engineers.
  • Effective communication for presenting results, writing technical documentation, and supporting regulatory submissions.
  • Knowledge of computer vision is a plus for multimodal applications (e.g., diagnostics, image-text synthesis)

    • (ref : hirist.tech)

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