Senior Analyst - Data Science

LatentView Analytics Ltd.; Bengaluru; On-site; INR 1,500,000 - 2,100,000; Full time

Job summary

LatentView Analytics Ltd. in Bengaluru is seeking a Senior Analyst - Data Science to lead Healthcare AI and Clinical Intelligence initiatives.

The role involves designing, training, and validating ML models for risk stratification, disease progression insights, and treatment recommendations. The position emphasizes feature engineering from longitudinal EHR data, processing unstructured records, and working with production deployment and monitoring to ensure real-world clinical validity and

Qualifications

• 3+ years of experience in data science or related field.
• Experience designing, training and validating ML models for healthcare applications.
• Strong proficiency in Python data science stack and SQL.

Responsibilities

• Design, train, and validate machine learning and statistical models focused on risk stratification, disease progression, treatment intelligence, and healthcare recommendations.
• Translate longitudinal clinical touchpoints into robust features for predictive models and generative AI systems.
• Build models and pipelines capable of extracting insights from unstructured healthcare records, doctor notes, and medical terminologies.
• Frame open-ended clinical questions into clear, measurable ML objectives; define data requirements and success metrics.
• Work with engineering teams to operationalize prototypes into production environments and establish continuous model performance tracking.
• Construct evaluation systems that assess offline metrics alongside real-world clinical validity, model calibration, algorithmic bias, and robustness.

Skills

Machine Learning & Statistical Mod

Python & Core Data Science Stack

Advanced SQL & Complex Querying

Large-Scale Longitudinal Data

Problem Formulation

Job description

Designation : Senior Analyst - Data Science

Level : L2

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.

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:

• Healthcare/EHR/Claims Data Processing & Clinical Ontologies
• Clinical NLP & Medical Language Models (including LLMs/Generative AI)
• Advanced Analytics: Time-Series Analysis, Survival Analysis, & Causal Inference
• Production ML Deployment & Performance Monitoring
• Technical Communication & Cross-Functional Stakeholder Alignment