HI, I'M ABU SIDDIQ
Bridging Financial Accounting with Data-Driven Business Analytics
About Me
HELLO.
I am Abu Bakkar Siddiq, a CPA Candidate and Dual MS student in Accounting Analytics and Business Analytics & Artificial Intelligence at The University of Texas at Dallas. I am currently actively seeking full-time opportunities in Accounting, Finance, and Business/Data Analytics where I can apply my 9+ years of professional experience to drive data-informed financial decision-making. My expertise spans financial reporting, general ledger accounting, ERP operations, and business analytics. I have hands-on experience with SAP S/4HANA, Oracle ERP, and QuickBooks for end-to-end financial transaction processing, complemented by Power BI, Tableau, SQL, Python, and R for data visualization, predictive modeling, and report automation. Beyond financial reporting, I have experience across the full accounting and finance lifecycle — from job costing, profitability analysis, and budget-to-actual variance analysis, to Accounts Receivable/Payable management, bank reconciliations, and vendor management. Across roles at Square Fashions Limited, Al-Madina Pharmaceuticals, and Novo Healthcare & Pharma, I have consistently delivered measurable improvements in cost control, collections efficiency, and process optimization. Complementing my accounting foundation, I value data-driven decision-making and reproducible analytical workflows. As a CPA Candidate, I have submitted my Application of Intent to the Texas State Board of Public Accountancy, and I continue to apply AI-driven tools and machine learning methods — including a fraud-detection classification project — to strengthen audit support, compliance, and financial risk analysis.
PROFESSIONAL
EXPERIENCE
Business Analyst Intern
May 2026 – July 2026
Dallas, TX, USA
Built DCF, NPV, IRR & ROI models for real estate and investment opportunities; supported budget vs. actual analysis.
Developed KPI dashboards in Power BI & Excel and prepared monthly/quarterly reports for senior leadership.
Analyzed market, competitive & operational data to support expansion and investment decisions.
Sr. Executive-Accounts and Finance
Jan 2022 to Dec 2024 · 3 yrs
Managed SAP S/4HANA transactions and financial reporting.
Built Power BI dashboards for sales and AR aging analysis.
Performed costing, profitability & cash flow analysis; improved margin by 12%.
Supported SAP implementation and training, improving efficiency by 20%.
Sr. Executive-Accounts and Finance
Prepared sales, bank reconciliation, collection & vendor reports for management.
Analyzed overhead variances using Power Query & Excel Solver, reducing costs by 10%.
Conducted inventory audits and stock aging analysis, reducing discrepancies by 15%.
Novo Healthcare and Pharma Ltd.
Managed full-cycle AR/AP, journal entries, payments & bank reconciliations in QuickBooks.
Developed sales & collection reports and improved receivables tracking efficiency by 10%.
Supported semi-annual internal audits, ensuring financial accuracy and control compliance.
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My aim is to revolutionize financial analytics by combining expertise with technology, ensuring that our clients not only keep pace with change but lead the way in their industries.
— Abu Bakkar Siddiq, Financial Data Scientist& CFA Candidate
EDUCATION
The University of Texas at Dallas, Richardson, Texas
- Master of Science in Business Analytics & AI
- Master of Science in Accounting Analytics
CPA Candidate (Texas)
National University of Bangladesh, Dhaka, Bangladesh
- Master of Business Studies, Accounting
- Bachelor of Business Studies, Accounting
- Exams in Progress
Skills & Expertise
Financial analysis, reporting, ERP systems, and data analytics focused on turning financial data into actionable business insights.
Blend financial expertise with cutting-edge analytics, ensuring our clients are equipped with actionable insights that enhance decision-making and maximize operational efficiency.
Publications
An Applied Business Analytics Framework for Fraud Detection Under Operational Constraints
Under Review · International Journal of Business and Data Analytics
Siddiq, A. B., & Ramezani, R. · Co-authored with Dr. Rasoul Ramezani, The University of Texas at Dallas · Submitted June 2026
Benchmarked XGBoost, CART, k-NN, and Logistic Regression under a CRISP-DM workflow;
XGBoost achieved ROC-AUC of 0.995 and PR-AUC of 0.894.
AI-Driven Business Analytics to Mitigate Risks in International Business Operations
Under Review · Contemporary Management Research
Siddiq, A. B. (First Author), Rafi, M. R., et al. · Under Review, 2026
Mixed-methods research combining 11 structured practitioner interviews across export manufacturing, logistics, fintech, retail, and global supply chain sectors with a systematic literature review, examining AI-driven analytics for
predictive risk identification, supply-chain resilience, and strategic decision-making.
Projects
Predicting Credit Card Fraud
January 2025 – May 2025 · Business Analytics with R
The University of Texas at Dallas
Key Contributions:
Built and compared Logistic Regression, Decision Tree, and k-NN models in R on 284,807 transactions, achieving 97%+ accuracy using SMOTE and ROC/AUC evaluation.
Identified fraud patterns around low-dollar transactions during late-night online and point-of-sale activity, informing real-time fraud alert thresholds.
Tools: R (caret, ggplot2, dplyr, ROSE), SMOTE, CRISP-DM
Financial Statement Analysis: Texas Instruments vs. Analog Devices
Spring 2025 · Intermediate Financial Accounting
The University of Texas at Dallas
Key Contributions:
Conducted comparative financial statement analysis of Texas Instruments and Analog Devices, evaluating liquidity, solvency, profitability, and efficiency ratios.
Assessed revenue trends, gross margins, R&D investment, and capital structure, translating findings into investment-relevant conclusions.
Tax Research Memorandum – Corporate Formation: Paul & Lisa (IRC §351)
Spring 2025 · Fundamentals of Taxation I
The University of Texas at Dallas
Analyzed corporate formation under IRC §§351, 358, and 362(e)(2), applying Treasury Regulations and relevant case law to evaluate nonrecognition and built-in loss limitations.
Identified tax consequences under two formation proposals and recommended a third-party pre-incorporation sale structure for optimal nonrecognition outcomes.
Tax Research Memorandum – ABC Corp. Dividend Reporting (IRC §316)
Spring 2025 · Fundamentals of Taxation II
The University of Texas at Dallas
Determined Form 1099-DIV classifications for $90M in corporate distributions using IRC §§301(c), 316(a), and applicable Treasury Regulations.
Applied the prorated current-year E&P deficit method to allocate $25M as ordinary dividends and $65M as non-dividend distributions.