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Saiesha Vemula

@saieshavemula

AI Data Analyst at Abbott Laboratories who built a predictive analytics pipeline that improved early anomaly detection accuracy by 34%.

United States

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At Abbott Laboratories, I engineered a Python predictive analytics pipeline with Scikit-learn and Pandas that improved early anomaly detection accuracy by 34%. I also automated clinical data workflows on AWS and created Power BI dashboards tracking operational KPIs.

At Orion Technolab, I developed customer churn models and automated executive reporting with Python and SQL. I also deployed Tableau dashboards and helped migrate reporting to Azure with Databricks and Apache Spark.

Experience

Work history, roles, and key accomplishments

Current

AI Data Analyst

Current

Abbott Laboratories

Aug 2025 - Present (1 year 2 months)

Engineered AI-powered predictive analytics pipelines and automated ETL workflows on AWS, improving anomaly detection accuracy by 34% and reducing manual data preparation time by 60%. Deployed Power BI dashboards and implemented NLP-based text analytics to drive business insights.

Python scikit learn Pandas AWS S3 Glue Redshift Power BI NLP LLM Prompt Engineering SQL CTEs Window Functions

Data Analyst

Orion Technolab

Jan 2021 - Jul 2023 (2 years 6 months)

Developed predictive models for customer churn forecasting, achieving 88% accuracy and reducing attrition by 19%. Automated reporting, designed Tableau dashboards, migrated to cloud data warehouse, and built ETL pipelines.