Skip to main content
Jenish Jiyani

Jenish Jiyani

Business Intelligence Engineer | Analytics Engineer | Data Analyst

Talent
Jersey CityMember since June 26, 2026
PythonSQLDAXMySQLSnowflakeAWS S3AWS AthenaLogistic RegressionXGBoostForecastingNumPyPandasScikit-learnPower BITableauReporting AutomationSHAP
·

Hire this person

Send a job offer directly to this candidate

PythonSQLDAXMySQLSnowflake

About

BI and Analytics professional with 4+ years building SQL, Python, AWS, Snowflake, Power BI, and Tableau solutions for large-scale business and healthcare datasets. Specialized in KPI engineering, ETL automation, forecasting, risk modeling, dashboard development, and stakeholder-facing decision support.

Experience

Business Intelligence Developer at DWIJA LLC (2025-01 – Present)

  • Built executive BI systems for user analytics, revenue tracking, forecasting, and KPI reporting using Python, SQL, Power BI, Tableau, AWS, and Snowflake.
  • Analyzed 20M+ monthly active user records to uncover behavior trends, campaign patterns, and sales opportunities, improving promotional sales performance by 24%.
  • Developed risk and sales forecasting models using logistic regression, XGBoost, and Python, improving forecast accuracy by 28% and reducing $35K in annual avoidable cost.
  • Automated recurring reporting pipelines and optimized AWS Athena queries on S3 datasets, reducing query runtime by 30% and saving 28 hours/month.
  • Designed Snowflake data models, Power BI dashboards, Tableau reports, and DAX measures for revenue, retention, campaign, and operational KPI tracking.

Data Analyst II at Scalelot Technologies (2020-01 – 2022-12)

  • Built healthcare analytics workflows for patient risk, ER operations, cost analysis, reporting automation, and data accessibility using Python, SQL, Power BI, MySQL, and AWS S3.
  • Analyzed 500K+ hospital records with Python, NumPy, Pandas, and SQL to identify patient-flow trends, cost patterns, and operational bottlenecks, improving analysis speed by 37%.
  • Developed high-risk patient classification models using logistic regression and XGBoost, improving early risk identification by 18% for clinical operations planning.
  • Designed ETL pipelines and automated weekly reporting workflows, reducing data processing time by 40% and manual reporting effort by 20%.
  • Created real-time Power BI dashboards with MySQL-backed reporting layers and DAX measures, reducing ER waiting time by 28% and improving data accessibility by 27%.

Education

Master of Science in Business Intelligence and Analytics – Stevens Institute of Technology (2024-12)

Bachelor of Science in Information Technology – Auro University (2022-05)

Skills

Business Intelligence EngineerAnalytics EngineerData Analyst

Reviews

Related