Financial Analyst - Data-Driven Finance Professional

LEELA MANIKANTA CHEEKATLA

667-***-**** *****.**********@*****.*** LinkedIn GitHub Maryland, USA PROFESSIONAL SUMMARY

Detail-oriented Financial Analyst with over 3 years of cross-functional experience in finance, operations, and data analytics across global service and supply chain environments. Proven expertise in preparing P&L reports, performing variance and cost analysis, and supporting month-end financial close processes. Skilled in building advanced Excel-based financial models, automating reporting workflows, and visualizing KPIs through Power BI and Tableau dashboards. Proficient in SQL, Python, and data validation techniques to ensure accuracy across large-scale financial datasets. Adept at collaborating with stakeholders to drive budgeting, forecasting, and continuous process improvement. Combines a strong technical foundation with financial acumen to deliver actionable insights that support strategic decision-making and business growth. Possesses strong analytical and communication skills, with advanced proficiency in Excel, essential for supporting daily P&L reporting and reconciliation. KEY SKILLS

• PROGRAMMING LANGUAGES: Python, R, SQL

• LIBRARIES & TOOLS: NumPy, Pandas, Matplotlib, SciPy, Scikit-learn, TensorFlow, Seaborn, Keras

• FINANCIAL & DATA ANALYSIS: P&L Reporting, Variance Analysis, Financial Modeling, Budgeting & Forecasting, Cost Analysis, Reconciliation, KPI Reporting, A/B Testing, Regression Analysis

• VISUALIZATION TOOLS: Tableau, Power BI, Advanced Excel (Pivot Tables, VLOOKUP, VBA, Power Pivot, INDEXMATCH), Power Query

• CLOUD PLATFORMS: Microsoft Azure, Amazon Web Services (AWS)

• DATABASES: PostgreSQL, MySQL, Oracle (PL/SQL), MongoDB

• ETL & DATA PIPELINES: SSIS, SSRS, Extract-Transform-Load (ETL) Processes, Data Wrangling, Data Validation

• METHODOLOGIES: Agile, SDLC, Waterfall

• DOCUMENTATION & OPERATIONS: SOP Documentation, Process Mapping, Root Cause Analysis, Requirements Gathering, Stakeholder Engagement, Audit Support

• OTHER TOOLS & CONCEPTS: Jira, Git, Microsoft Office Suite (Excel, Word, PowerPoint), ServiceNow PROFESSIONAL EXPERIENCE

INTERNATIONAL SOFTWARE SYSTEMS, INC., Greenbelt, MD Data Analyst May 2025 - Present

• Performed variance analysis on operational and logistics costs, identifying key drivers of budget deviations and recommending cost optimization strategies to improve margin efficiency.

• Developed financial forecasting models using historical shipment, procurement, and inventory data to support budgeting and strategic planning decisions.

• Partnered with finance teams to reconcile operational data with financial reports, ensuring accuracy in cost allocation, revenue alignment, and monthly close processes.

• Built executive-level Tableau dashboards presenting week-over-week financial and operational KPIs (cycle time, on-time delivery, error rates) for VP-level stakeholders.

• Analyzed supply chain operations using SQL and Tableau, implementing a performance framework that improved fulfillment speed by 14% across 6 distribution centers.

• Automated Excel-based financial and operational reports using VBA and Power Query, reducing manual effort by 60% and improving reporting accuracy.

• Conducted cross-functional workshops with operations, IT, and procurement teams to define KPIs and translate business requirements into actionable dashboards.

• Led integration of third-party carrier tracking data with internal systems using Python, enabling real-time exception tracking and improved cost visibility.

• Reduced shipment mislabeling incidents by 9% by optimizing barcode scanning workflows in collaboration with engineering and logistics teams.

• Created SOPs for operational processes, supporting standardization, compliance, and scalability across warehouse operations.

Epsilon Infinity Services HYDERABAD, INDIA

Financial Analyst Jan 2021 – June 2022

• Prepared and analyzed daily, weekly, and monthly P&L (Profit & Loss) reports, ensuring data accuracy and timely delivery to finance and operations leadership.

• Conducted variance analysis on revenue and expense trends across departments, identifying cost-saving opportunities and assisting in budget optimization efforts.

• Supported monthly and quarterly financial close processes, including account reconciliation, journal entry reviews, and accrual tracking, improving reporting efficiency.

• Built dynamic Excel-based financial models using advanced functions (VLOOKUP, INDEX-MATCH, PivotTables, Power Query, VBA) to forecast revenue, operating expenses, and margin impact.

• Collaborated with accounting teams to streamline reconciliation processes between internal systems and external vendor records, reducing discrepancies by 20%.

• Partnered with business units to collect financial inputs for budgeting and forecasting, resulting in more accurate planning cycles.

• Automated repetitive reporting tasks by integrating Power BI dashboards and scheduled Excel reports to monitor key financial KPIs and department spending.

• Performed data validation, cleansing, and consolidation of large financial datasets using SQL and Python, ensuring consistency across multiple financial systems.

• Monitored departmental spending against budget, producing variance reports and escalating major deviations to leadership.

• Assisted with the design and implementation of cost allocation models, enabling better visibility into resource usage across business functions.

• Created and maintained standard operating procedures (SOPs) for financial workflows, improving team knowledge transfer and audit readiness.

• Delivered financial performance updates and communication to leadership during monthly review meetings, providing insightful commentary on key variances, risks, and opportunities. PROJECTS

Strategic Inventory Analysis for Business Growth

• Built SARIMA and ensemble ML models Random Forest, Gradient Boosting, and XGBoost to forecast sales, achieving R : 0.733, RMSE: 5176.70, and MAE: 26.79M, improving demand prediction accuracy.

• Conducted thorough sales data analysis and item clustering, categorized all 13,000+ jewelry pieces, and personally trained the team on efficient stock management and demand forecasting for future.

• Developed a Power BI dashboard to visualize 5 years of sales data, analyze trends, and predict 2024 sales, aiding data-driven stock adjustments and growth.

Diabetic Retinopathy Detection- Publication

• Constructed a CNN-based classifier, automating DR detection through segmented retinal blood vessels, surpassing 92% accuracy using the STARE database, facilitating mass screening initiatives.

• Implemented contrast-limited adaptive histogram equalization for noise reduction and a two-step segmentation process using Fuzzy C-Means clustering and Region-based active contour, achieving an 85% similarity measure in blood vessel extraction.

• Integrated the trained CNN model into a streamlined workflow, enabling efficient processing of retinal images for real time DR detection and decision support in ophthalmology. EDUCATION

UNIVERSITY OF MARYLAND, BALTIMORE COUNTY Baltimore, MD Master of Professional Sciences in Data Science Aug 2022 - May 2022 HINDUSTAN UNIVERSITY Chennai, INDIA

Bachelor of Engineering in Computer Science June 2018 - May 2022

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