Sarah Ashley Creado
26 yrs oldTarget Roles
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Professional Summary
Business Analytics & AI graduate student with 3+ years of experience in finance, insurance, business analysis, data
analytics, and process improvement. Experienced in analyzing financial and operational data, reconciling transactions
across systems, developing Power BI dashboards and KPI reports, and improving manual reporting workflows. Skilled in
SQL, Power BI, Power Query, Advanced Excel, Python, Snowflake, and relational databases, with experience translating
business requirements into data-driven reporting and actionable insights.
Technical Skills
Education
Masters in Business Analytics and AI
Bachelors in Management Studies
Experience
The University of Texas at Dallas – Executive Education, Texas, USA
July 2025 - Present
Student Assistant – Data & Business Analytics
• Developed Power BI dashboards, KPI reports, and analytical views to monitor program performance, engagement,
and conversion trends.
• Analyzed operational and marketing datasets using SQL and Excel to identify trends, evaluate performance, and
support forecasting initiatives.
• Gathered stakeholder reporting requirements and translated business needs into data-driven reporting and
dashboard solutions.
• Performed data validation and quality checks across reporting workflows to improve accuracy and consistency.
• Delivered analytical insights and performance summaries to stakeholders to support data-driven planning and
business decisions.
• Maintained reporting documentation and supported continuous improvement of analytics and reporting processes.
Marsh McLennan Global Services - Guy Carpenter, Mumbai, India
September 2021 - June 2024
Claims Specialist – Reinsurance | Financial Analytics & Business Operations
• Analyzed financial, claims, and operational data across multiple systems to identify trends, discrepancies, and
opportunities to improve reporting accuracy and business performance.
• Reconciled 400+ financial transactions across systems, supporting data accuracy, financial reporting, compliance, and
approximately $35M in recovered revenue.
• Validated high-volume financial data and investigated discrepancies through root-cause analysis, improving data
integrity and reporting reliability.
• Developed recurring reports and analytical outputs for Finance, Operations, Compliance, and business stakeholders,
supporting performance monitoring and decision-making.
• Collaborated cross-functionally with Finance, Operations, Actuarial, and Compliance teams to gather requirements,
improve workflows, and resolve data and reporting issues.
• Identified manual process bottlenecks and implemented workflow improvements that reduced backlog by 60%,
improving operational efficiency and reporting turnaround.
Notable Projects
Salon Management System Database | Tools: PostgreSQL, SQL, ERD, Data Modeling
April 2025
• Designed and implemented a normalized PostgreSQL relational database with 6+ interconnected tables using ERD
modeling, DDL/DML, relationships, and business rules.
• Developed advanced SQL queries and views to analyze service demand, stylist performance, earnings, and
operational capacity.
• Applied data modeling and relationship design to support accurate reporting, resource planning, and operational
decision-making.
Geolocation Big Data Analytics | Tools: Hadoop, Spark, Hive, HDFS, SQL, Power BI
December 2025
• Built an end-to-end geolocation and logistics analytics pipeline using HDFS, Hive, Spark/PySpark, and SQL to process
large-scale datasets.
• Designed ETL/ELT workflows to clean, transform, and analyze data, identifying risk patterns, route inefficiencies, and
operational bottlenecks.
• Developed Power BI KPI dashboards and translated findings into recommendations for cost optimization, routing, and
operational efficiency.
AI-Powered Finance Process Automation | Alteryx, Power Apps, UI Path, AI
December 2025
• Designed an end-to-end intelligent document processing workflow using Alteryx, Power Apps, and UiPath to ingest,
classify, and extract data from unstructured financial/loan documents
• Applied AI-based classification to route documents by type, reducing manual triage
• Eliminated manual data-entry steps, reducing compliance risk exposure and processing time
Employee Attrition Analysis | Tools: R, Decision Trees, Logistic Regression, PCA
• Analyzed employee data to identify key drivers of attrition and workforce trends
• Built and evaluated predictive models (Decision Tree, Logistic Regression) achieving 82.5% accuracy
April 2026
• Delivered data-driven business recommendations to support HR retention strategies and workforce planning
• Translated analytical findings into actionable insights for improving employee satisfaction and reducing turnover.