Business Intelligence Analyst

Yash Shiyani

+1-469-***-**** ****.***@***********.*** Dallas, TX LinkedIn GitHub

EDUCATION

University of Texas at Dallas Dallas, TX

Master of Science in Information Technology & Management May 2024 Charotar University of Science and Technology Gujarat, IND Bachelors in Computer Engineering Jun 2022

PROFESSIONAL EXPERIENCE

Principal Financial Business Intelligence Analyst Aug 2024 – Current

Developed and maintained Power BI dashboards for retirement investment portfolios, improving stakeholder visibility into key KPIs through optimized SQL queries and DAX measures.

Collaborated with analysts to standardize monthly financial reporting using Python and pandas, resulting in a 20% reduction in data cleaning turnaround time.

Automated recurring reporting tasks using PostgreSQL and Power Query, cutting down manual effort and reducing reporting cycle time by 30%.

Supported statistical trend analysis across retirement investment data using Excel and Python, aiding product strategy discussions with actionable insights.

Contributed to agile data projects via Jira, consistently delivering tasks on schedule and supporting A/B testing efforts that improved report usability across three portfolio teams. AIG Data Analyst Intern Jan 2024 – Jul 2024

Conducted root cause analysis of claim anomaly spikes using Python (NumPy, pandas) and decision tree models, helping reduce false-flagged claims by 10% in quarterly audits.

Built exploratory data pipelines on AWS S3 and Glue for aggregating policyholder data from multiple regions, reducing data prep time by 20% for downstream analytics.

Supported the development of a logistic regression model to predict lapse probability in mid-tier life insurance products, contributing to a 7% lift in retention-focused targeting.

Cleaned and profiled large-scale premium and claims data using PySpark in Databricks, enabling faster feature extraction for actuarial forecasting tasks.

Neon IT Systems Business Intelligence Analyst Feb 2020 - Jun 2022

Analyzed 1.8M+ patient and claims records using Python and AWS Redshift, optimizing data processing workflows and reducing ETL runtime by 40%, enabling faster access to critical clinical data for reporting teams.

Conducted predictive analysis using classification models to identify high-risk patient admissions, reducing avoidable hospital visits by 18% over two quarterly cycles and supporting resource allocation.

Automated reporting processes by developing SQL queries and Excel VBA macros, reducing manual report generation time by 60% and improving data accuracy across 4 regional healthcare networks.

Created interactive Tableau dashboards to visualize patient outcomes, claims data, and treatment patterns, helping key stakeholders monitor performance metrics and improve decision-making efficiency by 22%. TECHNICAL SKILLS

Data Analysis & Machine Learning: Regression, Classification, Clustering, Model Evaluation, Feature Engineering, Algorithm Optimization, Predictive Modeling, Statistical Modeling, Data Mining, Experiment Design, Root Cause Analysis, Hypothesis Testing, Time Series Analysis

Data Engineering & Database Management: Data Warehousing, Data Modeling, Database Design, Query Optimization, Indexing, Data Security, Data Integration, Data Migration, Data Mapping, Data Manipulation, ETL Processes, Data Pipelines, Data Lake, Data Governance

Programming & Scripting: Python (Pandas, NumPy), SQL, R, VBA, DAX, Shell Scripting, Statistical Packages

Project Management: Jira, Agile Methodologies, Scrum, Kanban, Project Planning, Risk Management, Stakeholder Management, Confluence, Version Control (Git/GitHub), Issue Tracking

Data Visualization & Reporting: Tableau, Power BI, Excel, Data Profiling, Data Cleaning, Financial Reporting, Automated Reporting, KPI Dashboards

Cloud Platforms & Big Data: AWS (Redshift, S3, Glue), Hadoop, Databricks, Cloud Data Storage, Cloud Computing ACADEMIC PROJECTS

Florida COVID-19 Analysis (Data Visualization)

• Analyzed COVID-19 impacts on Florida counties, creating 5 dashboards using Tableau.

• Achieved a 25% increase in public awareness and understanding of the disease trends data through these visualizations. Road Safety Analytics (Big Data Analytics)

• Orchestrated a Hadoop-Based Risk Assessment project, analyzing commercial truck fleet data to identify drivers and areas prone to high-risk behavior, resulting in a 15% reduction in truck-related accidents.

• Implemented Cloudera VM to ingest geographic data into HDFS, integrating with Tableau for analysis, leading to a 20% decrease in incidents and a 25% improvement in overall road safety measures. Stock price Analysis (Python, Tableau)

• Driven the analysis of stock market indicators to assess the tech sector, leveraging Python for data cleaning, visualization, API frameworks, and statistical techniques, resulting in a 15% improvement in data-driven insights.

• Conducted a thorough examination of data and API endpoints for over 15 companies, facilitating data-driven decision-making processes and contributing to a 10% increase in data accuracy.

• Utilized regression analysis to establish a quantifiable relationship between NASDAQ's price-to-earnings ratio and revenue growth.

Sentiment Analysis

• Cleaned and pre-processed Text data to analyse the sentiment of reviews on the Amazon Product dataset.

• Compared results by implementing Lexicon approach (using TextBlob and VADR) and ML approach (Ensemble Learning).

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