DIVYA SARADE
Business/Data Analyst
About
Data/Business Analyst skilled in SQL, Advanced Excel, Python, Power BI, Qlik Sense, BI, KPI reporting, dashboard development, and data visualization. Experienced in data cleaning, transformation, analysis, business requirements, process improvement, stakeholder management, and data-driven decision-making. Hands-on experience with AI-powered analytics, Generative AI, machine learning, anomaly detection, and reporting automation.
Skills & Expertise (42)
Work Experience
Business/Data Analyst
Dexian India
Feb 2025 - Present
Contributed to the Magic Matching automation project for Bullhorn ATS, focused on automating candidate-job matching and improving recruitment workflow efficiency. Supported project planning, requirement gathering, scope definition, task prioritization, milestone tracking, and process documentation throughout the project lifecycle. Analyzed candidate profiles, job descriptions, skills, experience, and historical data to develop and validate data-driven matching logic and analytical rules. Collaborated with business stakeholders, technical teams, and project teams to gather requirements, clarify business needs, define acceptance criteria, and align project deliverables. Supported Agile/Scrum practices, including backlog refinement, sprint planning, daily stand-ups, sprint reviews, UAT, feedback incorporation, and continuous improvement. Tracked project tasks, deliverables, dependencies, issues, risks, and timelines to support on-time project execution. Performed data validation, gap analysis, root-cause analysis, and process mapping to identify workflow gaps and automation opportunities. Analyzed financial and transactional data, including vendor and invoice datasets, using SQL and Excel to identify trends, anomalies, data quality issues, and potential financial risks. Developed financial KPI reports and dashboards to monitor transaction volumes, vendor activity, exception trends, cost-related patterns, and operational performance, supporting data-driven business decisions. Performed variance and trend analysis on historical datasets to identify unusual patterns, investigate exceptions, and provide actionable insights for business and financial reporting. Analyzed matching results to identify false matches, missed matches, skill gaps, accuracy issues, and optimization opportunities. Used SQL to extract, join, filter, validate, and analyze candidate, job, skill, and matching datasets; performed data quality checks and analyzed matching accuracy, conversion trends, and exception cases. Developed Excel based analytical reports and KPI dashboards to track matching performance, automation outcomes, candidate-job match rates, process efficiency, and key project metrics, providing actionable insights to stakeholders. Coordinated UAT and testing activities, documented defects and feedback, validated outputs, and worked with technical teams on issue resolution. Used AI-assisted tools, SQL, and Excel for data preparation, analysis, matching validation, reporting, documentation, and workflow optimization. Prepared status updates, analytical reports, project documentation, and stakeholder communications to support project visibility and decision-making.
Data/Business Analyst
PRGX Global, Inc.
Jan 2024 - Jan 2025
Built and managed end-to-end ETL analytics pipelines, processing 100K+ financial, vendor, and transaction records for financial recovery, spend analysis, and fraud detection. Extracted, transformed, and loaded data from multiple sources using SQL and Qlik Sense load scripts, ensuring data accuracy, consistency, completeness, and reliable refresh cycles. Designed and optimized analytical data models, improving dashboard and report performance and reducing load time by approximately 20%. Performed data cleaning, validation, deduplication, standardization, and quality checks to improve the reliability and usability of financial datasets. Conducted time-series, trend, and variance analysis on historical transaction data to identify recurring patterns, seasonality, recovery leakage, abnormal spending, and financial performance trends. Analyzed vendor and transaction behavior to identify cost-saving opportunities, unusual spending patterns, and potential financial risks. Developed rule-based anomaly detection logic to identify suspicious transactions, including round-amount invoices, transaction spikes, missing purchase orders, and missing receipt details. Applied historical benchmarking and time-based analysis to identify deviations from normal transaction behavior and potential fraud indicators. Created custom KPIs, calculated measures, and analytical metrics to monitor fraud risk, vendor anomalies, transaction consistency, and financial recovery performance. Performed financial data analysis and exception analysis to identify high-risk transactions, vendors, and potential recovery opportunities. Collaborated with business stakeholders to translate financial recovery and fraud detection requirements into analytical rules, KPIs, dashboards, and reporting solutions. Monitored project progress, risks, issues, dependencies, and deliverables, providing status updates and analytical insights to support timely project execution. Automated recurring financial and management reporting workflows using Qlik Sense load scripts, SQL-based ETL, scheduled data refreshes, and automated KPI calculations, reducing manual data preparation and improving reporting consistency, turnaround time, and dashboard scalability. Designed and delivered interactive Qlik Sense dashboards with drill-downs, filters, KPIs, and time-based views to monitor financial recovery, fraud indicators, vendor performance, and transaction trends. Developed financial reporting and management dashboards to provide actionable insights into transaction patterns, recovery performance, vendor risk, and operational KPIs. Automated periodic and ad-hoc reporting workflows, improving reporting efficiency, data refresh reliability, scalability, and dashboard usability. Presented analytical findings and dashboards to stakeholders, translating complex financial datasets into clear business insights and data-driven recommendations. Worked in an Agile/cross-functional environment, supporting requirements gathering, analytical solution design, UAT, stakeholder feedback, and continuous improvement. Designed and implemented a Qlik Sense dashboard to detect fraudulent transactions in vendor and invoice data. Developed anomaly detection flags for round amounts, transaction spikes, and missing details. Improved fraud detection accuracy through efficient ETL processes and data visualization techniques.
Education
B.E. Computer Engineering - Indira College of Engineering and Management
2020 - 2024 · Afghanistan
HSC - KBP College
- 2020 · Afghanistan
SSC - DHK High School
- 2018 · Afghanistan
Certifications
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Skills (42)
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