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Sai Mounish Ramisetti

Data Analyst • Jersey City, NJ • m************@gmail.com • 551****510 • drivetube.ai/•••••

Professional Summary

Data Analyst with 4 years of experience delivering BI solutions, analytics, and applied ML to inform operational and financial decisions. Strong in Power BI and dashboard design, with hands-on experience implementing DAX measures and star-schema models to support sales, POS and supply-chain reporting. Proficient in Python (pandas, NumPy), SQL and scikit-learn for ETL, EDA, forecasting and supervised learning; built regression and tree-based models for transaction and project overrun analysis. Experienced integrating data via APIs from Jira, Tempo and transactional systems, and automating reporting pipelines with SQL Server and Power Apps. Comfortable presenting technical findings to C-level stakeholders and converting business requirements into reusable analytics products that drive process and forecasting improvements.

Technical Skills

Programming Language: Python,SQL
Databases: Microsoft SQL Server
Testing & QA: Quality Assurance,User Acceptance Testing
Data Warehousing: Star Schema
Data Analysis & Visualization: Pandas,NumPy,Matplotlib,Seaborn,Power BI,DAX,Regression,CART,Forecasting
Machine Learning & AI: Transformer,Random Forest,Feature Selection
AI/ML Frameworks & Libraries: scikit-learn,BeautifulSoup,python-pptx,GeneticSelectionCV
MLOps: Feature Engineering
Data Integration & ETL: ETL
Project Management & Collaboration: Jira
Enterprise Platforms: Power Apps

Work Experience

Newagez
Harrisonville, MO (Remote)
Data Analyst
06/2024 – Present
Supported retail operations analytics and reporting for sales, POS transactions and supply-chain processes to improve revenue tracking, forecasting and operational KPIs.
Tech Stack: Power BI, DAX, SQL Server, Power Apps, Python, pandas, scikit-learn, ETL pipelines
  • Partnered with sales, finance, and operations stakeholders to translate business requirements into Power BI report specifications and prioritized KPIs for revenue and cost analysis.
  • Designed star-schema data models and optimized SQL Server queries to enable faster ad-hoc analysis of regional performance and product trends.
  • Developed interactive Power BI dashboards and implemented DAX measures to visualize revenue drivers, product trends and operational metrics for executive reporting.
  • Automated ETL pipelines and integrated transactional data from SQL Server and Power Apps via API-driven workflows to ensure consistent operational reporting.
  • Analyzed POS transaction datasets using Python and pandas to identify customer behavior patterns, peak transaction windows, and payment method trends.
  • Built regression-based models with scikit-learn to quantify factors influencing self-checkout adoption and transaction time, informing operational adjustments.
  • Conducted SKU-level supply chain analysis using SQL and Python to surface inventory inefficiencies and recommend demand-forecasting improvements.
Studio Labs (Industry Capstone Program)
New York, NY
Business Data Analyst
01/2024 – 05/2024
Capstone consulting engagement analyzing fixed‑scope engineering projects to identify estimation variance and cost overrun predictors using integrated project tracking data.
Tech Stack: Python, scikit-learn, matplotlib, seaborn, GeneticSelectionCV, Jira, Excel
  • Extracted and integrated multi-source project data from Jira, Tempo, EazyBI and Excel using APIs and Python to construct reproducible data pipelines.
  • Engineered features, handled missing values and performed binary encoding to prepare datasets for supervised learning in scikit-learn.
  • Built and tuned CART and Random Forest models in scikit-learn to identify cost-overrun predictors, achieving 80% classification accuracy and surfacing high-impact features.
  • Performed feature selection using GeneticSelectionCV and permutation importance to reduce model complexity and prioritize actionable predictors.
  • Visualized estimated versus actual hours and cluster-based comparisons with matplotlib and seaborn to inform resource allocation and estimation improvements.
  • Presented analytic findings and technical recommendations to C-level stakeholders, translating model outputs into prioritized process and estimation changes.
Anira Solutions
Hyderabad, India
Business Analyst Trainee
05/2021 – 11/2022
Delivered operational reporting, data validation and dashboarding to support business users and improve data consistency across reporting workflows.
Tech Stack: SQL, Power BI, Excel, QA, UAT
  • Translated operational requirements from business users into technical specs for recurring reports and KPI dashboards.
  • Wrote and optimized SQL queries to extract, clean and validate large datasets for downstream reporting and analysis.
  • Designed and maintained Power BI and Excel dashboards to monitor operational KPIs and surface actionable insights for managers.
  • Reviewed data collection workflows and recommended standardization to reduce inconsistencies across distributed datasets.
  • Developed process documentation and reporting handoff materials to ensure continuity and accelerate new-analyst onboarding.
  • Drove QA and UAT testing to validate report outputs against source systems and resolved discrepancies prior to deployment.

Projects

Data Classification and Feature Optimization | 05/2023
Tools Used: Python, scikit-learn, GeneticSelectionCV, matplotlib, seaborn, R, Excel
  • Applied GeneticSelectionCV-based feature selection on a 30-variable tumor dataset to identify the most predictive features and reduce model complexity.
  • Implemented Linear Discriminant Analysis in R and Excel Solver with a customized penalty function to prioritize minimizing critical misclassification errors.
  • Evaluated model performance in Python using scikit-learn and visualized results with matplotlib and seaborn, achieving 92% classification accuracy.
Autonomous PPT Generator | 08/2021 – 05/2022
Tools Used: Python, BeautifulSoup, transformers, python-pptx
  • Built an end-to-end Python pipeline using BeautifulSoup to scrape, preprocess and classify web content into clean, model-ready inputs.
  • Benchmarked transformer models (BART, XLNet, BERT) for abstractive summarization using ROUGE metrics and selected BERT based on consistency and hallucination risk assessment.
  • Automated slide generation with python-pptx by integrating BERT-summarized content and images to produce validated, structured PowerPoint outputs.
POS Transaction Analytics and Customer Behavior Analysis | 06/2024
Tools Used: Python, pandas, NumPy, scikit-learn, SQL
  • Analyzed point-of-sale transaction logs using Python, pandas and NumPy to identify purchasing patterns, peak transaction periods and payment trends.
  • Performed data preprocessing and exploratory analysis to derive checkout efficiency metrics and customer-segmentation insights.
  • Developed regression models in scikit-learn to quantify factors influencing self-checkout adoption and transaction duration, informing operational changes.
Supply Chain Analytics and Demand Forecasting | 07/2024
Tools Used: Python, SQL, Forecasting
  • Performed supply chain analytics across supplier performance, inventory and production processes to identify SKU-level inefficiencies.
  • Analyzed historical demand and inventory patterns using SQL and Python to detect forecasting gaps and supplier performance trends.
  • Developed analytical reports and KPI-driven insights to support demand planning and production optimization recommendations.

Education

Stevens Institute of Technology
Master’s in Business Intelligence and Analytics — GPA: 3.83/4 • Hoboken, United States • 01/2023 – 05/2024
Visvesvaraya National Institute of Technology
Bachelor of Technology in Electronics and Communications Engineering • Nagpur, India • 08/2018 – 05/2022

Certifications

PL-300: Power BI Data Analyst Associate — Microsoft
Six Sigma Green Belt — Kennesaw State University

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