Abhigna Kunta

Machine Learning & Data Engineer | Python, SQL, PySpark | AWS, Azure, Snowflake | Scalable ML Pipelines, NLP, MLOps | Healthcare Data & AI

Role
Ml Data Scientist at Johnson & Johnson
Location
Dallas-Fort Worth, TX, US
LinkedIn followers
500 followers
Information TechnologyView LinkedIn profile

About Abhigna Kunta

Data Analyst with 4+ years of experience working across healthcare, finance, and…

Experience

  1. Ml Data Scientist

    Johnson & Johnson

    Jan 2025 — Present · US

    Designed and deployed scalable ML pipelines for clinical data integration using Python, PySpark, and SQL on AWS S3, Glue, and Redshift, improving model training throughput by 35% and enabling near real-time predictions for 1M+ patient records- Developed readmission and risk stratification models with XGBoost, Logistic Regression, and scikit-learn, improving ROC-AUC from 0.81 → 0.89 and supporting value-based care decisions across provider networks- Automated data ingestion and transformation from FHIR and HL7 sources into Snowflake using Airflow + dbt, reducing manual ETL workload by 40 hours/month and ensuring HIPAA-compliant traceability- Built a clinical NLP pipeline using spaCy and BERT to extract diagnoses, symptoms, and medication intents from unstructured EHR notes, cutting manual coding time by 50% and enhancing data completeness- Collaborated with physicians and data governance teams to implement model explainability (SHAP, LIME) and bias monitoring dashboards in Tableau, strengthening regulatory transparency for FDA and payer audits- Containerized and deployed ML microservices using Docker and Kubernetes with CI/CD automation via GitHub Actions, reducing deployment time by 60% and improving reproducibility across environments.

Education

  • University of North Texas

    Masters, Advance data Analytics

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Abhigna Kunta — Ml Data Scientist at Johnson & Johnson in Dallas-Fort Worth, TX, US | Unifers