Data Analyst Financial

Amaresh Perugu

Data Analyst

*************@*****.*** LinkedIn 312-***-**** Chicago, IL

Data Analyst with 4+ years of experience in transforming complex financial data into actionable insights through SQL, Python, and business intelligence tools. Proven expertise in automating reporting workflows, performing variance analysis, and building interactive dashboards using Tableau and Excel VBA. Strong background in financial data auditing, reconciliation, and cross-functional collaboration with risk and compliance teams. Holds a Master’s in Computer Science with published research in deep learning and sentiment analysis, combining academic rigor with real-world impact in data-driven decision-making. PROFESSIONAL EXPERIENCE

Data Analyst Northern Trust Apr 2024 – Present

Consolidated and transformed datasets from multiple internal systems using SQL and Python, resolving schema mismatches and standardizing over 120+ data fields, improving report accuracy across five business units.

Developed automated reporting solutions using SQL and Excel macros, replacing manual weekly processes and reducing preparation time by 35%, resulting in faster insight delivery to senior stakeholders.

Audited over 8,000 financial records across ledgers, vendor transactions, and department logs; corrected inconsistencies that improved month-end close accuracy and reduced reconciliation delays by 2 days.

Designed 10+ interactive dashboards in Tableau to visualize asset performance, budget consumption, and investment movement, supporting leadership with clear and actionable data views.

Developed end-to-end documentation for data pipelines and reporting frameworks while analysing business processes to identify inefficiencies, resulting in a 15% reduction in reporting errors and improved cross-team alignment.

Recorded data lineage and transformation logic for each ETL process to maintain transparency and support audit compliance reviews.

Partnered with internal audit and risk teams to validate model outputs, reducing post-review errors and improving confidence in financial reports across business stakeholders.

Data Analyst 7FinCorp Group Aug 2019 – Aug 2022

Processed and catalogued large-scale datasets from various financial systems to support monthly reporting, correcting 1,000+ data inconsistencies, which raised reporting reliability and lowered error rates by 20%.

Engineered automated Excel dashboards using VBA to monitor key financial indicators, cutting manual report compilation time by 40% and accelerating department-level decision timelines.

Assessed budget and transaction data through variance analysis, uncovering anomalies that led to forecast adjustments across three divisions, and presented insights through intuitive visual summaries.

Optimized SQL-based data extraction processes for business-critical requests, reducing query execution time by 25%, and streamlining access for multiple teams.

Partnered with finance and IT to embed data validation protocols, bolstering data integrity and enhancing alignment with intern al control frameworks, thereby minimizing reporting gaps and audit flags.

Investigated behavioral patterns in customer transactions to detect early indicators of fraud, contributing to a 15% reduction in financial losses through timely escalation to risk units.

Reconciled records from multiple accounting platforms during monthly closes, improving consolidation accuracy and shortening closing timelines by three days.

RESEARCH & PUBLICATIONS

Twitter Data Preprocessing for Sentiment Analysis

Published in TEST Engineering and Management, Jan–Feb 2020 (ISSN: 0193-4120). This paper focused on structuring raw Twitter datasets and optimizing preprocessing techniques, enhancing the data quality for downstream sentiment classification. Enhanced Twitter Sentiment Analysis Using Deep Learning Methods

Published in International Journal of Advanced Science and Technology, Vol. 29(7). Explored the use of artificial neural networks to improve sentiment prediction accuracy, achieving a measurable performance gain over traditional classification approaches. EDUCATION

M.S in Computer Science, DePaul University Aug 2022 – Jun 2024 B.E in Computer Science and Engineering, Saveetha University May 2016 – Jun 2020 TECHNICAL SKILLS

Programming & Scripting: Python, SQL, VBA, R, Java

Data Analysis & Processing: Pandas, NumPy, Excel (Advanced), Power Query, Data Cleansing, Data Transformation

Databases: MySQL, PostgreSQL, Microsoft SQL Server

Business Intelligence & Visualization: Tableau, Power BI, Excel Dashboards

Machine Learning & Deep Learning: Scikit-learn, TensorFlow, Keras, Artificial Neural Networks (ANN)

Big Data & ETL Tools: Apache Spark, Hive, AWS Glue (if applicable), Data Pipelines

Statistical Methods: Variance Analysis, Hypothesis Testing, Trend Analysis

Tools & Platforms: Git, Jupyter Notebook, Google Colab, Microsoft Office Suite

Reporting & Automation: Excel Macros, Automated Reporting Systems, Data Validation

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