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Jadala Poorna Prasad

Aspiring Business Analyst • Bengaluru, Karnataka • p***********@gmail.com • +91*******996 • linkedin.com/••••• • drivetube.ai/•••••

Career Objective

Business Analyst with 0 years of experience transitioning from a Computer Science background; skilled in requirement gathering, process analysis, stakeholder communication, and data-driven decision making. Applied machine learning and statistical evaluation in an independent bioenergy forecasting project to translate technical results into business recommendations for sustainable energy planning.

Education

Saveetha School of Engineering
Bachelor of Engineering (B.E.), Computer Science • Chennai • Jun 2020 – Sep 2025
Sri Chaitanya Jr. College, Tirupati
Intermediate (Class XII) • Tirupati • Jun 2018 – May 2020

Technical Skills

Programming Languages: Python
Frameworks and Libraries: scikit-learn,TensorFlow,Keras,Pandas,NumPy,Matplotlib,Seaborn
Databases: SQL,Database Querying
Data and Analytics: Time Series Forecasting,LSTM,Random Forest,Data Visualization,MS Excel
Tools and Methodologies: Jupyter Notebook,Google Colab,Git,GitHub
Business Analysis: Requirement Gathering,Process Analysis & Design,Use Case Modeling,Business Process Mapping,Stakeholder Communication,KPI Definition,Functional Requirement Documentation,User Acceptance Testing UAT Support
Concepts & Methods: Identity & Access Management IAM Concepts,Model Evaluation Metrics,Statistical Analysis,Data-Driven Decision Making

Projects

Bioenergy Forecasting & Optimization Analysis
Tools Used: LSTM, Random Forest, Python, scikit-learn, TensorFlow, Pandas, NumPy, Matplotlib, Time Series Forecasting, Model Evaluation Metrics
  • Led end-to-end analysis comparing LSTM and Random Forest approaches to identify the most reliable method for predicting bioenergy output, directly supporting planning decisions for sustainable energy initiatives.
  • Designed and executed 20 experimental runs across two model groups, applying accuracy, error metrics, and confidence-interval analysis to validate model performance and robustness.
  • Achieved and reported a top model accuracy of 97.07% (deep-learning approach), translating technical model outcomes into a clear business recommendation favoring deep learning for operational forecasting.
  • Produced a business-focused evaluation documenting cost and planning implications, enabling non-technical stakeholders to understand trade-offs and supporting adoption decisions for forecasting tools.

Certifications

Tata Cybersecurity Security Analyst Job Simulation (Identity & Access Management) — Forage • Dec 2025
Internet of Things (IoT) — NPTEL
Blockchain Technology — NPTEL

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