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Machine Learning (ML) / Data Science Expert

Indian School of Business

Hyderabad · On-site Full-time 2w ago

About the role

Position Details

  • Number of Positions: 1
  • Location: Hyderabad
  • Reports to Position: PI/Co-PI
  • Reportees to Position: None
  • Band: FT

About the Institute

Max Institute of Healthcare Management is an interdisciplinary research centre at ISB that provides insights on healthcare delivery and management to policymakers, public institutions, and corporates to enable the creation of better health systems through integrated elements of research, education and outreach.

Job Description

Job

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

  1. Reviewing AI solutions, training datasets, and algorithm documentation
  2. Validating and benchmarking model performance and fairness metrics
  3. Ensuring compliance with data security and privacy standards
  4. Developing and testing data pipelines to support pilot deployments
  5. Conducting hands‑on validation of AI outputs against clinical decisions
  6. Supporting field teams in interpreting model outputs
  7. Collaborating with clinical and operations experts to adapt models to real‑world contexts
  8. 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

Job Interface / Relationships

Internal

  • MIHM Research and Admin team
  • Other departments including Grants, Finance, Legal, and IT

External

  • Grantor research/programme team
  • Vendors & Consultants
  • Sub‑grantees/data collection agencies
  • IRB Boards, governments, other stakeholders

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 on‑site 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

How to Apply?

Send an email to maxinstitute@isb.edu with the subject line “Application for ML Expert” and attach a copy of your CV. Any evidence of written work and references by academics would be a strong positive. Applications will be reviewed until the position is filled. You will be contacted only in case you are shortlisted for an interview.

Contact Information

Hyderabad Campus
Indian School of Business
Gachibowli, Hyderabad – 500111

  • Timings: Monday‑Friday, 08:00 AM IST to 06:00 PM IST
  • Phone: 040 23187777 / 0172 4591800
  • Email: careers_hyderabad@isb.edu

Mohali Campus
Indian School of Business
Knowledge City, Sector 81, SAS Nagar, Mohali – 140 306

Requirements

  • 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
  • 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

Responsibilities

  • 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

Skills

AIComputer ScienceData ScienceMachine LearningNLPPython

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