AI Data Scientist

About XpertDox
XpertDox, Inc. is a physician-founded, venture-backed healthcare AI company headquartered in Scottsdale, Arizona, with a global delivery team in India. Our platform, XpertCoding, autonomously codes outpatient medical claims directly from clinical documentation using neural networks, machine learning, and natural language processing.
Position Summary
You will work on neural network models that read clinical documentation and predict medical codes. Your first job is diagnosis: finding out why these models get specific cases wrong, and testing fixes until one holds up. Once a fix is proven, you write it into production code that runs inside the automated coding pipeline. This is an individual contributor role with no team management. It suits someone who wants to understand model errors and fix them. It does not suit someone who wants to run experiments without shipping, or who works only in notebooks.
Key Responsibilities
In this role you will:
Own diagnosis of model errors on clinical text: find where predictions go wrong and trace each pattern to its root cause.
Design experiments that test one specific fix at a time, and decide from the results whether the fix moves forward.
Train, fine-tune, and evaluate neural network models for multilabel classification on clinical documentation.
Improve precision on imbalanced classes, where a wrong code has a real cost.
Write production Python that moves proven fixes into the automated coding pipeline.
Explain the tradeoffs of a proposed change to the AI Team Lead before it touches a production model.
Document every experiment: what you tried, what happened, and what you decided.
Required Qualifications
At least 1 year of hands-on machine learning work outside coursework.
Hands-on experience fine-tuning pretrained language models for text classification.
Project work training deep learning models in Python.
Experience with multilabel classification, including handling class imbalance.
Production Python: code that runs inside a larger system, beyond notebook experiments.
Strong debugging and root-cause skills: you can work out why a model or pipeline is behaving unexpectedly.
Willing to act on partial evidence instead of waiting for exhaustive experiments.
Explains tradeoffs clearly before making a change.
Methodical and careful, because this work affects real claims.
Preferred Qualifications
Making model predictions reliable enough for automated decisions.
Adapting language models to specialized vocabulary.
Taking a model from research prototype to production deployment.
Location and Schedule
This role is on-site at the XIPL office in Noida, Monday through Friday, 12:30 PM to 9:30 PM IST. It is not remote and not hybrid. Candidates outside Noida must relocate to Noida before their start date. No travel is required.
Compensation
Base salary of ₹20 to ₹30 lakh per year, commensurate with experience.
Relocation assistance, reimbursed against receipts, up to a cap.
Benefits
Health insurance, provident fund, and leave per XIPL policy.
Company cab service for all Noida employees.
To Apply
Apply at https://careers.xpertdox.com/
XIPL is an equal opportunity employer.

Work arrangement
No