Summary
Overview
Work History
Education
Skills
Websites
Certification
Languages
Accomplishments
Work Availability
Timeline
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JAYVEEN PATEL

JAYVEEN PATEL

Data Analyst
Dallas,TX

Summary

Results-driven Data Analyst with 3+ years of experience in transforming complex data into actionable insights across healthcare and financial domains. Skilled in SQL, Python, and R for data extraction, cleaning, and statistical analysis. Proficient in developing ETL workflows, predictive models, and interactive dashboards using Power BI and Tableau. Experienced in collaborating with cross-functional teams to support data-driven decision-making. Strong background in machine learning, data visualization, and regulatory compliance in agile environments.

Overview

4
4
years of professional experience
2
2
Certification

Work History

Data Analyst

Mckesson Corporation
, TX
06.2024 - Current
  • Designed and implemented automated ETL pipelines using Python to ingest over 2 million patient records from EMR systems and Komodo Health's claims database, improving data availability for downstream analytics by 65%.
  • Wrote complex SQL Server queries to standardize and join clinical datasets, including lab results, diagnosis codes, and treatment history, streamlining data preparation and reducing manual processing time by 40%.
  • Applied Python (pandas, NumPy) to clean and transform high-dimensional data, ensuring consistency across features used in machine learning models that supported early-stage cancer detection.
  • Developed over 100 engineered features from structured data and implemented correlation filtering and variance thresholding, improving model performance and increasing predictive sensitivity from 76% to 87%.
  • Built and validated classification models (Random Forest, XGBoost) using scikit-learn, optimizing hyperparameters through cross-validation and reducing false negatives by 21% in cancer risk predictions.
  • Created interactive Tableau dashboards to present patient risk stratification and geographic trends, enabling faster decision-making and reducing clinical reporting time from 3 days to under 6 hours.
  • Partnered with clinical, compliance, and product teams to ensure all data processes adhered to HIPAA regulations, contributing to two successful audits and supporting a 20% increase in early cancer referral rates during pilot deployment.

Data Analyst

Cybage Software
01.2021 - 07.2023
  • Consolidated over 50 million transaction records and 3 million customer profiles into a centralized SQL Server data warehouse, establishing a reliable foundation for fraud analytics and real-time monitoring.
  • Developed and automated ETL workflows using SQL Server Integration Services (SSIS) and Python to clean, transform, and standardize large datasets from diverse financial systems, reducing data processing time by 40%.
  • Implemented machine learning models in Python (Isolation Forest, DBSCAN, Local Outlier Factor) to detect anomalous transaction patterns, improving fraud detection accuracy by 28% and minimizing false positives.
  • Designed real-time Power BI dashboards to track suspicious transactions, high-risk accounts, and regional fraud trends; enabled compliance teams to respond within 10-15 minutes, significantly reducing financial risk.
  • Translated fraud risk indicators into SQL-based logic and analytical models, enabling early identification of high-risk transactions and contributing to a 35% increase in proactive fraud detection.
  • Performed historical fraud case analysis using Python (pandas, seaborn, matplotlib) to identify behavioral trends and system vulnerabilities, which led to the discovery of three previously undetected fraud methods.
  • Implemented security protocols in Power BI and SQL, including role-based access control and data masking, to ensure compliance with GDPR and internal data governance policies during cross-functional reporting.

Education

Master of Science - Business Analytics

East Texas A&M University

Bachelor of Science - Computer Science

Devi Ahilya Vishwavidyalaya University

Skills

  • SDLC
  • Agile
  • Waterfall
  • Kanban
  • Lean Six Sigma
  • Python
  • SQL
  • R
  • Visual Studio Code
  • PyCharm
  • Jupyter Notebook
  • NumPy
  • Pandas
  • Matplotlib
  • SciPy
  • Ggplot2
  • TensorFlow
  • Seaborn
  • Scikit-learn
  • Tableau
  • Power BI
  • Advanced Excel
  • MySQL
  • SQL Server
  • PostgreSQL
  • Oracle
  • Microsoft Azure
  • SAS
  • Ad hoc Report
  • EDA
  • ETL Tools
  • Informatica Power Center
  • Machine Learning Algorithms
  • Deep Learning
  • NLP
  • Big Data Technologies
  • Spark
  • Probability distributions
  • Predictive Modelling
  • Hypothesis Testing
  • Regression Analysis
  • Linear Algebra
  • Advance Analytics
  • SSIS
  • SSRS
  • SSMS
  • Data Mining
  • Data warehousing
  • Data transformation
  • Clustering
  • Classification
  • Regression
  • A/B Testing
  • Forecasting & Modelling
  • Data Cleaning
  • Data Wrangling
  • Jira
  • Confluence
  • GitHub
  • Bitbucket
  • Windows
  • Linux
  • Mac OS

Certification

  • Microsoft Azure Data Fundamentals (AZ-900)
  • Microsoft Azure AI Fundamentals (AI-900)

Languages

English
Native or Bilingual

Accomplishments

  • At McKesson, designed and automated ETL pipelines using Python and SQL to ingest over 2M patient records, improving data availability by 65% and reducing manual processing time by 40%.
  • At McKesson, enhanced predictive model performance for early-stage cancer detection by engineering 100+ features and applying Random Forest and XGBoost, increasing sensitivity from 76% to 87% and reducing false negatives by 21%.
  • At Cybage Software, built a centralized SQL Server data warehouse integrating 50M+ transactions and 3M+ customer profiles, enabling real-time fraud analytics and contributing to a 35% rise in proactive fraud detection.
  • At McKesson and Cybage, developed interactive dashboards using Tableau and Power BI to monitor patient risk and fraud trends, cutting clinical reporting time from 3 days to 6 hours and enabling fraud response within 15 minutes.
  • At Cybage Software, implemented anomaly detection models (Isolation Forest, DBSCAN, LOF) in Python, improving fraud detection accuracy by 28% and uncovering previously undetected fraud patterns.
  • At both McKesson and Cybage, ensured data governance aligned with HIPAA and GDPR, contributing to successful audits and enabling secure, compliant cross-functional reporting.

Work Availability

monday
tuesday
wednesday
thursday
friday
saturday
sunday
morning
afternoon
evening
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Timeline

Data Analyst

Mckesson Corporation
06.2024 - Current

Data Analyst

Cybage Software
01.2021 - 07.2023

Master of Science - Business Analytics

East Texas A&M University

Bachelor of Science - Computer Science

Devi Ahilya Vishwavidyalaya University

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