Senior Data Scientist

1 day ago


Faridabad, Haryana, India MediElaj Full time ₹ 12,00,000 - ₹ 36,00,000 per year

Key Responsibilities

  • Design, build, and deploy end-to-end machine learning solutions across structured (tabular) medical datasets and unstructured/non-tabular data (text, images, OCR, signals).
  • Apply advanced ML, deep learning, and LLM-based approaches to solve real-world healthcare/medical challenges.
  • Collaborate with cross-functional teams (engineering, product, domain experts) to translate business requirements into scalable data science solutions.
  • Drive MLOps best practices: experiment tracking, model versioning, CI/CD, monitoring, and automated retraining pipelines.
  • Ensure production-grade robustness using
    Test-Driven Development (TDD)
    and
    OOP principles
    in ML pipelines.
  • Contribute to architecture discussions and mentor junior team members.

Technical Skills & Requirements

  • Strong proficiency in
    Machine Learning, Deep Learning, and Statistical Modeling.
  • Expertise in handling
    tabular medical data
    (EHRs, lab reports, prescriptions) and
    non-tabular data
    (text, imaging, audio).
  • Experience with
    LLMs
    (fine-tuning, prompting, integration with downstream tasks).
  • Hands-on experience with
    MLOps frameworks and practices
    :
  • MLflow, DVC, Airflow, Kubeflow, Weights & Biases
  • Model deployment and monitoring in production
  • Strong software engineering skills:
    Python, SQL, TDD, OOP, design patterns.
  • Containerization & orchestration:
    Docker, Kubernetes (nice-to-have)
    .
  • Familiarity with cloud platforms (
    AWS / GCP / Azure
    ) for scalable ML solutions.
  • Knowledge of medical data compliance standards (HIPAA, GDPR) is a plus.

Preferred Frameworks/Tools

  • ML/Deep Learning:
    scikit-learn, PyTorch, TensorFlow, Hugging Face, XGBoost, LightGBM
  • NLP/LLMs:
    Transformers, LangChain, RAG pipelines
  • MLOps:
    MLflow, DVC, Airflow, Kubeflow
  • Data Processing:
    pandas, PySpark, SQL, Polars

Soft Skills

  • Strong problem-solving and analytical mindset.
  • Ability to explain technical concepts to non-technical stakeholders.
  • Leadership and mentorship capabilities.


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