Abhijeeth Reddy Bhavanthula
Data Analyst • Dallas, Texas, USA • a***************@gmail.com • +19******014 • linkedin.com/••••• • abhijeethreddy.com/•••••
Professional Summary
Data Analyst with 3+ years of experience delivering financial and operational analytics using SQL, Python and Power BI. I design ELT pipelines in BigQuery and Python, build DAX-driven Power BI reports and automate reconciliation workflows to support month-end close and forecasting. I have implemented Informatica- and Talend-based ETL improvements in consulting engagements, analyzed 10M+ monthly transactions to tune fraud thresholds, and migrated fragile Excel processes into repeatable Python/SQL pipelines. I combine statistical methods (RFM, K-means) and forecasting to reduce variance and surface actionable cohorts for business users. I regularly present findings to VP-level finance and operations stakeholders and deploy Power Automate/Power Apps to reduce manual effort and increase self-serve analytics adoption.
Technical Skills
Programming Language: Python,SQL
Databases: Google BigQuery
Data Analysis & Visualization: Pandas,Power BI,DAX,Power Query,Forecasting
Machine Learning & AI: K-Means
AI/ML Frameworks & Libraries: scikit-learn
Data Integration & ETL: Informatica,ELT
ERP & Supply Chain Systems: SAP,Workday
Compliance & Governance: SOX Compliance
Project Management & Collaboration: Agile,Scrum
Enterprise Platforms: Power Automate,Guidewire
Marketing Analytics: RFM Analysis
Work Experience
Farm Bureau Financial Services (FBFS)
Dallas, Texas, USA
Data Analyst
Feb 2025 – Present
Worked on finance and operations analytics at a regional insurance firm; built reporting and ELT systems to support month-end close, forecasting, and operational dashboards.
Tech Stack: Power BI, DAX, Python, BigQuery, SQL, Power Automate, Guidewire, JD Edwards, Workday
- Built 8 Power BI dashboards with 25 DAX measures to replace manual Excel reporting and enable self-serve finance analytics.
- Designed and maintained ELT pipelines using Python and BigQuery to aggregate financial data from Guidewire, JD Edwards, and Workday, automating ingestion and saving 8 hours weekly.
- Automated GL reconciliation checks using SQL and Python across large account populations, strengthening SOX controls and reducing month-end rework.
- Developed a Power BI forecasting model trained on labeled GL data that reduced forecast variance ~11% during recurring budget reviews and informed VP-level decisions.
- Deployed Power Automate workflows and a Power App to automate report distribution, cutting recurring manual steps and improving access for business users.
- Presented analyses and dashboards to finance and operations stakeholders, translating model outputs into actionable budget adjustments and control improvements.
Accenture
Telangana, India
Data Analyst
Feb 2022 – Jul 2023
Delivered analytics and ETL modernization for banking, insurance and 3PL clients in consulting engagements; supported fraud detection tuning, reconciliation and supply-chain reporting.
Tech Stack: Python, SQL, Informatica, Power BI, SAP
- Analyzed 10M+ monthly financial transactions using Python and SQL to profile transaction patterns and surface high-risk signals.
- Tuned fraud detection thresholds using Python and SQL, reducing false-positive alerts by 15% and improving investigation throughput.
- Re-engineered 20+ SQL queries and Informatica ETL jobs to reduce dashboard refresh time from 45 minutes to under 20 minutes.
- Delivered SAP-sourced supply chain analytics in Power BI for a 3PL client, building measures and visuals to track fulfillment and reduce order-cycle escalations.
- Rebuilt the banking ledger reconciliation process from fragile Excel macros into a Python and SQL automated pipeline with configurable business rules and email-based exception reporting.
- Partnered within Agile teams to prioritize analytics deliverables and accelerate deployment cycles.
Projects
Banking KPI & Forecasting Dashboard
Tools Used: Power BI, SQL, Excel, DAX, Power Query
- Built a Power BI forecasting dashboard using SQL and Excel to track banking KPIs and budget variance across multiple business units.
- Implemented DAX time-intelligence measures and automated refresh workflows to enable finance stakeholders to self-serve recurring variance and scenario analysis.
Customer Segmentation & RFM Analysis
Tools Used: Python, scikit-learn, Pandas, K-means
- Built a customer segmentation model using Python and K-means to identify behavioral patterns and population cohorts for targeted action.
- Profiled segment coverage and signal overlap across transaction data to surface high-risk and high-value customer groups.
Education
Belhaven University
MS in Information Technology Management • Aug 2023 – May 2025
Certifications
Microsoft Azure Fundamentals – AZ-900 — Microsoft
Google Data Analytics Professional Certificate — Google
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