Akash Perni Portfolio

Hi,
I'm Akash Perni

I'm a

Seeking Full-Time Opportunities in the Data Science/Engineering/Analytics Domain | MS Software Engineering @umd | Data Analyst at UMD | Data Science Intern at Cognizant | AWS cloud intern at AICTE | Expertise in Data Science, Data Analysis, Data Engineering, ETL pipelines, ML, Deep Learning and AWS.

About Me

Data Analyst | Aspiring Data Scientist

Hello! I’m Akash Perni, a Graduate with a Master’s degree in Software Engineering from the University of Maryland College Park, with a strong foundation in data analytics & engineering, machine learning, ETL pipelines and AWS cloud. I’ve worked as a Data Analyst at the University of Maryland and previously interned at Cognizant, where I designed predictive models, built data pipelines, dashboards, and worked with big data tools like Spark, Kafka, and Airflow.

I’m passionate about solving real-world problems and continuously learning new tools and technologies to sharpen my analytical edge. I’m currently seeking full-time roles in data science or analytics where I can apply my skills to drive data-informed decisions and deliver business impact.

Experience

Sep, 2023 - Aug, 2024

Data Analyst - University of Maryland

Performed exploratory data analysis (EDA) and data preprocessing on multiple projects, identifying patterns, anomalies, and optimizing data quality for predictive modeling.
Collaborated with a team on the Traffic Flow Optimization with Airflow, and Kafka project, contributing to the design and implementation of an ETL pipeline that processed and analyzed 500000+ real-time traffic records from multiple toll operators.
Engineered machine learning models to analyze traffic congestion patterns, generating insights that optimized traffic light timing, leading to a 10% reduction in congestion on simulated datasets.

Apr, 2023 - Aug, 2023

Data Science Intern - Cognizant

Led exploratory data analysis (EDA) on large datasets, identifying key trends, outliers, and correlations, leading to data-driven insights that improved decision-making efficiency by 20%.
Built and deployed predictive machine learning models, optimizing loan approval project and increasing accuracy by 14%, integrating techniques from Logistic Regression, Random Forest and XGBoost.
Designed and implemented Tableau dashboards, providing real-time insights for stakeholders and boosting data-driven decision-making by 20%.

Aug, 2021 - Dec, 2022

Data Analyst UG Assistant - VVIT

Analyzed 5,000+ student demographic and User records to help the career center better understand student engagement patterns and set data-driven goals for future program improvements.
Developed reports, Tableau and PowerBI dashboards to visualize key trends in student engagement and course review ratings, providing insights to enhance academic programs and improve course offerings.
Assisted faculty in analyzing data from 10+ college events, festivals, and sports activities using Excel tools like PivotTables and VLOOKUP, uncovering student participation trends and boosting engagement by 18%.

Mar, 2022 - May, 2022

AWS cloud intern - AICTE

Deployed and managed a scalable web application by creating a MySQL RDS database with an Auto Scaling group and Application Load Balancer (ALB), optimizing EC2 instances for efficient performance, resulting in a 15% increase in uptime during peak loads.
Improved system efficiency by implementing a LAMP stack on Amazon Linux 2 and seamlessly importing data into the RDS instance using Cloud9 IDE, enhancing data accessibility and system reliability by 10%.

Education

2023 - 2025

Master of Engineering in Software (SE) - University of Maryland College Park

CGPA - 3.91/4

Relevant Courses: Software engineering, Software Design and Implementation, Data Science, Analytics for Decision Support, Machine learning.

Services: Worked as a Teaching Assistant (TA) and Graduate Course Aide for the course “INST314: Statistics for Information Science,” supporting over 300+ students in discussions and academic activities.

2019 - 2023

B.Tech in Information Technology (IT) - VVIT

CGPA - 3.98/4

Relevant Courses: Python, R, SQL, Data Science, Operating Systems, Machine Learning, DBMS, Big Data Analytics, Advanced Mathematics, Statistics.

Achievements: Top 5% of the class, Chairman's club member, 4x Academic Excellence Award

Tech Stack

Languages and Databases

Python, R, SQL, MySQL, PostgreSQL, MySQL, MongoDB, Data Structures, Oops

Domain Skills

Pandas, NumPy, Matplotlib, Plotly, Seaborn, TensorFlow, Scikit-learn, Machine Learning, CNN's, Data Extraction & Analysis
ETL & ELT pipelines , Apache Airflow, Apache Kafka, Apache Spark, DAG, KPI’s
Streamlit, Sentiment Analysis, Statistical Modelling, Time Series, Recommendation systems

Software & Tools

AWS, Snowflake, Tableau, PowerBI, Git/GitHub, Ms Excel, Ms Powerpoint, VS Code, Agile, Scrum

Latest Projects

Crop Wise

Intelligent Crop recommendation system using Machine Learning.

CineMatch

A content filtering movie recommendation engine based on Machine Learning.

Chatstat

A web application that analyze your WhatsApp chat data. It provides message statistics, word clouds, emoji analysis, and more.

COVID-19 Vaccine Tracker Dashboard

A dynamic and interactive Tableau visualization project designed to monitor and analyze the global distribution of COVID-19 vaccines.

USA Software Engineering Job's Analysis

This project explores the US Software Engineering job market by leveraging machine learning algorithms to classify job salaries based on a variety of features.

Hi, I'm Akash Perni