Job Overview

To evaluate, validate, and operationalize AI/ML models for real-world healthcare applications ensuring accuracy, fairness, and compliance.

Job Purpose

The Machine Learning / Data Science Expert position offers an excellent opportunity to apply advanced analytical and technical skills in evaluating and deploying AI models within real-world healthcare settings. The Expert will be responsible for

- Reviewing AI solutions, training datasets, and algorithm documentation
- Validating and benchmarking model performance and fairness metrics
- Ensuring compliance with data security and privacy standards
- Developing and testing data pipelines to support pilot deployments
- Conducting hands-on validation of AI outputs against clinical decisions
- Supporting field teams in interpreting model outputs
- Collaborating with clinical and operations experts to adapt models to real-world contexts
- Contributing to capacity-building and documentation of AI evaluation methods

Job Specifications

Knowledge / Education:

- MS/PhD in Computer Science (preferred); OR a Postgraduate Diploma in Data Science combined with an undergraduate degree in Engineering, Statistics, Mathematics, or related discipline

Specific Skills:

- Strong organizational and communication skills to work across diverse technical, clinical, and research teams
- Excellent project management and organizational skills

- Meticulous attention to detail
- Ability to work independently and to carry out assignments to completion within parameters of instructions given, prescribed routines, and standard accepted practices
- Capability to manage multiple tasks efficiently
- Demonstrated ability to manage relationships with partner organizations
- Willingness to frequently travel to study sites to support pilot deployments

Mandatory Experience:





- Minimum 3 years of experience in AI/ML model development, validation, and evaluation with large, real-world datasets
- Hands-on experience building and validating AI/ML models in one or more of these areas: predictive modeling, classification, natural language processing, or computer vision applications
- Experience in applying fairness, bias, and equity assessments in ML models
- Familiarity with data management, ML pipeline development, and IT system integration processes
- Knowledge of model explainability and interpretability tools
- Knowledge of data security, privacy, and regulatory compliance requirements

Key Responsibilities

- Conduct desk reviews of AI solutions including evaluation of training datasets, algorithm choices, and model construction
- Assess retrospective performance metrics, calibration, and bias mitigation approaches; establish benchmarks
- Ensure compliance with reporting standards and data security/privacy guidelines
- Support pilot deployments by validating data pipelines and monitoring real-time model performance. with site-travel as required
- Facilitate training sessions for deployment teams on the interpretation and utilization of AI outputs

- Work with in office teams to test model outputs in real-world settings and integration into user workflows
- Conduct hands-on validation of model performance at pilot sites (e.g., comparing outputs with clinical decisions)
- Collaborate closely with clinical experts, operations specialists, and researchers to ensure models are relevant and actionable in real-world settings

Locations

Hyderabad

Mohali

Disclaimer: This has been sourced from a public domain and may have been modified by Naukri.com to improve clarity for our users. We encourage job seekers to verify all details directly with the employer via their official channels before applying.

📌 Machine Learning professional (Hyderabad)
🏢 Indian School of Business u0026 Finance (ISBF)
📍 Hyderabad