.png){kind=logo}
Pavithra Shankar
Mid-level QA Engineer specializing in AI/ML model validation and data quality
Connect with Pavithra
Pavithra already has a relationship with Reval, so a warm intro from us gets a much better response than cold outreach.
Recommended
Already have an account?
About
ML practitioner with a QA background who has built end-to-end ML pipelines for a health risk prediction use case (lifestyle + demographics), emphasizing robustness through strict data validation, leakage prevention, and cross-validation. Collaborated with a dietician to sanity-check predictions and refine feature interpretation for real-world practicality; has not yet deployed LLM/AI systems to production and has no hands-on orchestration framework experience but is willing to learn.
Experience
Education
Key Strengths
- Built end-to-end ML pipelines used in real workflows
- Strong focus on preventing data leakage via validation and cross-validation
- Addresses data quality issues (missing values, class imbalance) and model stability
- QA-driven approach to reliability: edge-case testing and failure-focused validation
- Iterative model selection approach; tested multiple models and finalized on XGBoost
- Effective collaboration with non-technical domain expert (dietician) to validate and refine feature usefulness
Discover more candidates like Pavithra
Search across thousands of pre-screened, high-quality, high-intent candidates on Reval.
Search Talent