Data Scientist HealthPlix Bangalore

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

Job summary

HealthPlix is seeking a Data Scientist to develop machine learning models and AI solutions using real-world healthcare data, including EHRs, notes, and prescriptions.

You will build, validate, and deploy predictive models for clinical outcomes and risk assessment, collaborating with clinicians and engineers to productionize pipelines.

Qualifications

• 2-6 years of experience in data science, machine learning, applied statistics, or 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, real-world datasets.
• Strong analytical, problem-solving, and communication skills.

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

ML modelling

Experimentation

Model evaluation

Communication

Tools

Pandas

NumPy

Scikit-learn

PyTorch

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.