Designation : Senior Analyst - Data Science

Level : L2

Location : Bengaluru

Experience : 3+ years

Job Role : Data Scientist – Healthcare AI & Clinical Intelligence

Responsibilities :

Model Development & Prototyping: Design, train, and validate machine learning and statistical models focused on risk stratification, disease progression, treatment intelligence, and healthcare recommendations.
Longitudinal EHR Feature Engineering: Translate temporal clinical touchpoints—such as diagnostic records, symptoms, lab investigations, and prescriptions—into robust features for predictive models and generative AI systems.
Unstructured Data Pipeline Design: Build models and pipelines capable of extracting insights from unstructured healthcare records, doctor notes, and medical terminologies.
Problem Scoping & Hypothesis Testing: Frame open-ended clinical questions into clear, measurable machine learning objectives; define appropriate targets, data requirements, and success metrics.
Production Integration & Monitoring: Work alongside engineering teams to operationalize prototypes into production environments and establish continuous model performance tracking.
Comprehensive Model Evaluation: Construct evaluation systems that assess offline metrics alongside real-world clinical validity, model calibration, algorithmic bias, and robustness.
Cross-Functional Collaboration: Partner with domain experts (clinicians) and technical stakeholders to ensure solutions directly enhance healthcare delivery and operational outcomes.

Required skills :

Primary Skillset:

Machine Learning & Statistical Modeling (Model Design, Evaluation, Calibration)
Python & Core Data Science Stack (Pandas, NumPy, Scikit-learn, PyTorch or similar)
Advanced SQL & Complex Querying
Working with Large-Scale, Messy & Longitudinal Data
Problem Formulation (Translating ambiguous domain/business problems into concrete ML setups)

Secondary Skillset: