Summary
Hitaishi Bairapureddy
Atlanta, Georgia +1-234-***-**** ***********@*****.*** LinkedIn GitHub
Portfolio
Financial Analyst with a Master’s in Business Analytics and a Bachelor’s in Agricultural Economics. Skilled in financial modeling, forecasting, variance analysis, econometrics, and risk assessment, with 5+ years of experience in SQL, Python, R, Power BI, and Tableau. Adept at building financial dashboards, cost-benefit models, and econometric analyses to support investment, budgeting, and strategic planning decisions. Proven ability to translate financial and economic data into actionable insights for executives and stakeholders.
EDUCATION
Kent State University, Ohio, United States Jan 2024 - May 2025 Master of Science, Business Analytics
• GPA: 3.94
• Achievements:
• Assisted in research on peatland NEE optimization (Univ. of Cambridge), contributed to a Goodreads deep learning project, and supported an automobile image annotation project using deep learning.
• Coursework: Data Visualization, Machine Learning, Database Management, Business Analytics, Data Mining Pondicherry University, Pondicherry, India Jan 2021 - Oct 2021 Bachelor of Science, Agri Economics
• GPA: 3.80
• Coursework: Data Analytics, Statistics, Agriculture Business Management, Agriculture Economics, Computer Applications PROFESSIONAL EXPERIENCE
Local Grown Salads Jun 2025 - Present
System Architect Philadelphia, PA
• Engineered the Agronomist subsystem for robotic greenhouses, enabling sensor-driven workflows, IoT data pipelines, and real-time decision-making.
• Developed comprehensive financial and operational dashboards in Power BI and Excel to monitor supply chain costs, operating expenses, ROI, and profit margins, improving financial visibility for senior leadership.
• Engineered and automated ETL pipelines (SQL, AWS, PostgreSQL, Dataiku) to integrate financial, IoT, and supply chain datasets, improving reporting accuracy and processing efficiency by 25%.
• Conducted variance analysis, capital expenditure evaluations, and cost-benefit studies to compare projected budgets with actual outcomes, enabling data-driven decisions that optimized operational spending.
• Partnered with cross-functional teams in finance, operations, and data science to design holistic performance frameworks combining financial KPIs with operational efficiency measures.
• Identified and implemented cost-saving strategies through detailed root cause and sensitivity analyses, which contributed to reducing downtime and improving margins in robotic greenhouse operations. Kent State University Jan 2024 - May 2025
Research Assistant Kent State University, OH
• Researched environmental and literary datasets, optimizing Net Ecosystem Exchange (NEE) in peatland sites across England and modeling user engagement trends in Goodreads data.
• Applied advanced econometric methods including time-series forecasting (ARIMA, GARCH, VAR), panel data regression
(fixed and random effects), GLS, probit/logit regression, and cointegration/error correction models (ECM) to analyze environmental and economic datasets.
• Built predictive models in R, Python, and MATLAB to measure long-term economic impacts of climate change, improving model interpretability using SHAP, LIME, and PDP visualizations.
• Conducted forecasting simulations to predict economic outcomes under multiple scenarios, supporting academic publications and policy recommendations.
• Designed SQL pipelines and used Python-based feature engineering for preprocessing large-scale financial and environmental datasets (millions of records).
• Collaborated with faculty and research partners to present findings on risk assessment, investment decision-making, and economic optimization strategies for environmental sustainability.
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Pivox labs Sep 2022 - Nov 2023
Financial Analyst Guntur, India
• Designed and maintained financial dashboards using SQL, Tableau, and Power BI to track logistics expenses, operating costs, revenue, and cash flows, supporting monthly and quarterly reporting cycles.
• Built financial forecasting models to project demand, optimize resource allocation, and reduce inefficiencies in supply planning.
• Automated recurring financial reporting workflows with SQL and Excel VBA, reducing manual reporting time by 40% and enabling faster decision-making.
• Conducted detailed variance analysis and cost-benefit evaluations on supply chain processes, identifying gaps between budgeted and actual performance, which led to margin improvement strategies.
• Partnered with business stakeholders to define financial data definitions, data flows, and reporting standards, ensuring compliance and consistency across reporting frameworks.
• Delivered insights that supported budget planning, investment evaluations, and risk assessments, enabling leadership to make financially sound decisions.
Karo Startup Jan 2022 - Aug 2022
Growth Managing Intern Delhi, India
• Conducted market research and financial feasibility studies to guide startup expansion, incorporating competitor benchmarking and investment viability.
• Designed financial and performance dashboards tracking KPIs such as CAC (Customer Acquisition Cost), ROI, customer engagement, and operational efficiency.
• Prepared financial models and revenue forecasts that projected 30% higher engagement profitability by optimizing marketing spend and resource allocation.
• Assisted in financial risk analysis for expansion projects, ensuring compliance with legal and regulatory standards.
• Provided data-backed recommendations to improve content strategy, acquisition costs, and long-term revenue growth. Pondicherry University Jan 2021 - Apr 2021
Field Agronomy & Data Intern Pondicherry, India
• Mapped backward and forward supply chains across 100+ farmers, retailers, and FPOs, identifying inefficiencies in distribution.
• Conducted applied econometric analysis (OLS regression, logit/probit, panel data models, ARDL) to study crop yields, pricing strategies, and farm-level profitability
• Implemented time-series and ARIMA models to forecast agricultural production trends and financial implications.
• Designed Excel dashboards to track irrigation frequency, fertilizer use efficiency, and pest control costs, allowing for data-driven farm management.
• Partnered with farmers and stakeholders to recommend cost reduction strategies and revenue optimization methods, improving agricultural profitability and sustainability.
• Compiled economic and financial reports integrating field-level data with broader supply chain and market insights. ANALYTICS PROJECTS
SQL Database and Data Analytics Project
Oracle SQL Server, Excel
• Developed a full-cycle data analytics project involving data import, database creation, complex query writing, and SQL documentation.
• Executed requirement gathering, data cleaning, processing, and analysis using SQL.
• Designed and created an interactive dashboard in Excel, summarizing key business insights.
• Enabled decision-makers to track business KPIs, improving reporting efficiency by 35%.
• Simulated end-to-end ETL flow using SQL queries to transform and load business-critical data. Performance Report Dashboard
Power BI
• Developed an interactive performance report dashboard using Power BI.
• Increased data reporting efficiency by 20%.
• Integrated various data sources to provide comprehensive insights and real-time analytics.
• Conducted in-depth data analysis to identify key performance indicators (KPIs) and trends. Predictive Modelling of Health Insurance Charges
R Studio, Power BI
• Developed a predictive model for health insurance charges.
• Performed data pre-processing and exploratory data analysis, including univariate, bivariate, and multivariate analysis, and created a dashboard in Power BI.
• Built regression and econometric models in R and Power BI; used ANOVA, PCA, and cost-risk analysis to forecast insurance premiums and evaluate risk-adjusted pricing.
• Implemented predictive analytics using linear regression and decision tree models.
• Evaluated model performance with metrics such as RMSE, MSE, and cross-validation. Financial Statement Forecasting & Valuation Model Python, R, Excel, Power B
• Developed a 3-statement financial model (Income Statement, Balance Sheet, Cash Flow Statement) to forecast company performance under multiple economic scenarios.
• Applied time-series econometric methods (ARIMA, VAR, GARCH) and regression analysis to forecast revenue growth, expense trends, and working capital needs.
• Conducted sensitivity and scenario analysis on key drivers such as interest rates, inflation, and commodity prices to assess their impact on profitability and valuation.
• Built a DCF (Discounted Cash Flow) model to estimate intrinsic value, incorporating weighted average cost of capital (WACC) and risk-adjusted discount rates.
• Designed interactive dashboards in Power BI to visualize financial projections, ROI, and valuation outcomes for executive decision-making.
TECHNICAL SKILLS
• Core Competencies: Data Analytics, Business Intelligence, Stakeholder Collaboration, Requirements Gathering, Data Flows & Documentation, Testing Concepts (Functional, Non-Functional, Performance), Problem-Solving, Agile & Scrum, Growth Mindset, Training & Mentoring
• Financial Analysis & Econometrics
Financial Modeling Time Series Forecasting (ARIMA, ARDL, GARCH, VAR) Panel Data Analysis (Fixed/Random Effects, GLS) Cointegration & Error Correction Models Probit & Logit Regression Econometrics Cost-Benefit Analysis Budgeting
& Forecasting Risk Assessment Variance Analysis ROI Analysis Capital Investment Evaluation
• Data Visualization & Business Intelligence: Power BI (DAX, Power Query, Drill through, Bookmarks), Tableau (Calculated Fields, Level of Detail (LOD) Expressions, Data Blending, Parameter Actions, Dashboard Actions), Excel Dashboards (PivotTables, Slicers), KPI Reporting, Report Portfolio Expansion
• Data Analysis & Management: Microsoft Excel (Advanced Formulas, PivotTables, VBA Macros), Celonis (Process Mining), RStudio, Jupyter Notebook, MATLAB, Data Lake Architecture, Dataiku (Visual Data Preparation, Automated Machine Learning, Feature Engineering, Data Pipeline Automation, Scenario Management, Collaborative Analytics), Alteryx (Data Preparation, Workflow Automation, Predictive Tools), Optimization, Generative AI, API Integration (REST APIs)
• Programming Languages: Python (Pandas, NumPy, Matplotlib, Seaborn, Scikit-learn, TensorFlow), R (tidyverse, ggplot2, caret, lubridate)
• Databases & Querying: SQL (MySQL, Oracle SQL, Postgres), Alation (Data Cataloging & Discovery), NoSQL (MongoDB), ETL development using SQL, Data Modeling & Architecture Design, Semantic Layer Development, Data Integrity & Quality Control, Postgres SQL(Pgadmin)
• Database Administration: User Role Management, Database Backup & Recovery, Performance Tuning, Index Optimization, Query Optimization, Database Security Policies, Scheduled Jobs & Automation, Data Integrity & Normalization
• Analytics & Machine Learning: Predictive Modeling, Statistical Modeling, Hypothesis Testing, Linear & Logistic Regression, Clustering (K-Means, Hierarchical), Classification (K-NN, Naive Bayes, Decision Trees), A/B Testing, Time Series Forecasting, Principal Component Analysis, Exploratory Data Analysis, ROC & AUC, Cross-Validation, Feature Selection & Engineering, Anomaly Detection
• Cloud & Data Governance: Microsoft Azure, Alation (Data Governance & Stewardship), Data Quality Frameworks, AWS (Redshift, S3, EC2), Data Governance Frameworks, Security Policy Compliance
• Reporting & Documentation: Data Flows, Data Definitions, Technical Documentation, MS PowerPoint, Jira (Agile Reporting), Canva
CERTIFICATIONS
• Lean Six Sigma certification: LinkedIn Learning.
• SQL & Data Analytics Certification: Coursera
• Excel Expert Certification (PivotTables, VBA, Advanced Formulas): LinkedIn Learning
• Machine Learning using R: Data Camp
• Python Programming – Nihar Skills Education
• Financial Econometrics: Time Series & Panel Data – Coursera
• Macroeconomic Forecasting Using Econometrics – edX
• Generative AI Fundamentals – Databricks.