Data Scientist

HealthPlix; Bengaluru; On-site; INR 1,200,000 - 2,400,000; Full time

Job summary

HealthPlix in Bengaluru is hiring a Data Scientist to develop machine learning models and AI solutions from real-world healthcare data. You will build and evaluate models for clinical prediction, risk assessment, and patient outcomes, collaborating with clinicians and engineers to deploy solutions into production.

Requirements: 2–6 years in data science, strong Python and SQL, and experience with Pandas, NumPy, Scikit-learn, PyTorch or similar libraries.

Qualifications

• 2-6 years of relevant data science experience.
• Proficiency in Python and SQL.
• Experience with Pandas, NumPy, Scikit-learn, PyTorch.
• Experience with large healthcare datasets and EHR is preferred.

Responsibilities

• Develop and evaluate machine learning and statistical models for clinical prediction, risk assessment, and patient outcome prediction.
• Analyze large-scale Electronic Health Record (EHR) data to understand patient journeys, disease progression, treatments, and clinical outcomes.
• Build models and pipelines using structured and unstructured healthcare data, including clinical notes and prescriptions.
• Apply techniques such as time-series modelling, NLP, recommendation systems, and risk prediction.
• Conduct experiments, validate model performance, and ensure accuracy, reliability, and robustness.
• Collaborate with ML engineers, clinicians, product managers, and data engineers to deploy models into production.

Skills

Python

SQL

Pandas

NumPy

Scikit-learn

PyTorch

NLP

Time-series

Communication

Tools

Spark

Job description

We are looking for a Data Scientist to develop machine learning models and AI solutions using real-world healthcare data.

Responsibilities:

• Develop and evaluate machine learning and statistical models for clinical prediction, risk assessment, and patient outcome prediction.
• Analyze large-scale Electronic Health Record (EHR) data to understand patient journeys, disease progression, treatments, and clinical outcomes.
• Build models and pipelines using structured and unstructured healthcare data, including clinical notes and prescriptions.
• Apply techniques such as time-series modelling, NLP, recommendation systems, and risk prediction.
• Conduct experiments, validate model performance, and ensure accuracy, reliability, and robustness.
• Collaborate with ML engineers, clinicians, product managers, and data engineers to deploy models into production.

Requirements:

• 2-6 years of experience in data science, machine learning, applied statistics, or a related field.
• Strong proficiency in Python and SQL.
• Experience with Pandas, NumPy, Scikit-learn, PyTorch, or similar libraries.
• Strong knowledge of machine learning, statistical modelling, experimentation, and model evaluation.
• Experience working with large, complex, and real-world datasets.
• Strong analytical, problem-solving, and communication skills.

Good to Have:

• Experience with healthcare data, EHR, or medical claims.
• Knowledge of Clinical NLP, LLMs, or Generative AI.
• Experience in longitudinal data modeling, survival analysis, causal inference, or recommendation systems.
• Experience with Spark or other large-scale data processing technologies.
• Experience deploying and monitoring machine learning models in production.