I am a B.Tech graduate in Data Science and Artificial Intelligence, passionate about data analytics, machine learning, and AI-driven solutions. I have hands-on experience with Python, SQL, Pandas, NumPy, Scikit-learn, Power BI, and Tableau. I have worked on projects involving kidney stone detection using CNN and SVM with Explainable AI, sales performance analysis, and used-car market analysis. These experiences have helped me develop my analytical thinking, problem-solving, and technical skills. I am continuously learning and exploring new technologies to strengthen my expertise. I aspire to build a career in Data Science, Data Analytics, or AI/ML, where I can turn data into meaningful insights and contribute to impactful projects.
Experience
Data Analyst Intern (Virtual)
VaidSys Technologies
Jul 2025 – Aug 2025
Cleaned and engineered features across an online retail dataset of 500,000+ transaction records, resolving nulls/duplicates and deriving metrics (TotalPrice, InvoiceMonth, Hour, DayOfWeek) using Pandas. Conducted EDA using Matplotlib and Seaborn to uncover top-selling products, monthly/hourly sales trends, and day-wise revenue patterns, informing inventory and promotional timing decisions. Performed RFM (Recency, Frequency, Monetary) customer segmentation to identify high-value customer groups, visualizing segment distributions via pie and bar charts to guide targeted marketing
Education
Dr. M.G.R. Educational and Research Institute
B.Tech in Data Science and Artificial Intelligence, Data Science
2022 – 2026 · Grade: 8.5/10
St. Ann's Matriculation Higher Secondary School
HSC, Computer Science with Maths
2021 – 2022 · Grade: 84.6%
St. Ann's Matriculation Higher Secondary School
SSLC, General
2019 – 2020 · Grade: 90.2%
Projects
Kidney Stone Prediction Using CNN and SVM: A Comparative Study
Python
CNN
SVM
Matplotlib
Seaborn
Built a kidney stone detection system from medical imaging data, designing and comparing CNN and SVM classification models for diagnostic performance
HR Analytics Dashboard (Power BI)
Power BI
Power Query
DAX
Excel
Engineered an interactive HR Analytics dashboard in Power BI using Power Query for data transformation, tracking KPIs including Employee Count, Attrition Rate, and Employee Experience
Multi-Module Weather and Disaster Prediction System (ML/NLP)
Python
NLP
Pandas
NumPy
Matplotlib
Seaborn
Built a 3-module system: weather forecasting from temperature/humidity/pressure data, NLP-based natural disaster prediction from news text, and flight delay estimation from airline/route/schedule data
Certifications
Data Science with Python
IBM
Data Analytics (Forage)
Deloitte
Data Visualization (Forage)
TATA
Excel Data Analysis
Coursera
Akshaya S
Data Science & AI Graduate | Aspiring Data Scientist | Python | SQL | Machine Learning | Power BI | Data Analytics
Chennai · https://www.linkedin.com/in/akshaya-shankar-503052296 · https://github.com/Akshayas05
About
I am a B.Tech graduate in Data Science and Artificial Intelligence, passionate about data analytics, machine learning, and AI-driven solutions. I have hands-on experience with Python, SQL, Pandas, NumPy, Scikit-learn, Power BI, and Tableau. I have worked on projects involving kidney stone detection using CNN and SVM with Explainable AI, sales performance analysis, and used-car market analysis. These experiences have helped me develop my analytical thinking, problem-solving, and technical skills. I am continuously learning and exploring new technologies to strengthen my expertise. I aspire to build a career in Data Science, Data Analytics, or AI/ML, where I can turn data into meaningful insights and contribute to impactful projects.
Experience
Data Analyst Intern (Virtual)
Jul 2025 – Aug 2025
VaidSys Technologies
Cleaned and engineered features across an online retail dataset of 500,000+ transaction records, resolving nulls/duplicates and deriving metrics (TotalPrice, InvoiceMonth, Hour, DayOfWeek) using Pandas. Conducted EDA using Matplotlib and Seaborn to uncover top-selling products, monthly/hourly sales trends, and day-wise revenue patterns, informing inventory and promotional timing decisions. Performed RFM (Recency, Frequency, Monetary) customer segmentation to identify high-value customer groups, visualizing segment distributions via pie and bar charts to guide targeted marketing
Education
Dr. M.G.R. Educational and Research Institute
2022 – 2026
B.Tech in Data Science and Artificial Intelligence, Data Science · Grade: 8.5/10
St. Ann's Matriculation Higher Secondary School
2021 – 2022
HSC, Computer Science with Maths · Grade: 84.6%
St. Ann's Matriculation Higher Secondary School
2019 – 2020
SSLC, General · Grade: 90.2%
Projects
Kidney Stone Prediction Using CNN and SVM: A Comparative Study
Python, CNN, SVM, Matplotlib, Seaborn
Built a kidney stone detection system from medical imaging data, designing and comparing CNN and SVM classification models for diagnostic performance
HR Analytics Dashboard (Power BI)
Power BI, Power Query, DAX, Excel
Engineered an interactive HR Analytics dashboard in Power BI using Power Query for data transformation, tracking KPIs including Employee Count, Attrition Rate, and Employee Experience
Multi-Module Weather and Disaster Prediction System (ML/NLP)
Python, NLP, Pandas, NumPy, Matplotlib, Seaborn
Built a 3-module system: weather forecasting from temperature/humidity/pressure data, NLP-based natural disaster prediction from news text, and flight delay estimation from airline/route/schedule data
Skills
Python
SQL
Tableau
Power BI
Pandas
NumPy
Matplotlib
Seaborn
Excel
DAX
Power Query
Predictive Modeling
Classification
Regression
CNN
SVM
Feature Engineering
Model Evaluation
Exploratory Data Analysis (EDA)
Data Cleaning
RFM Analysis
NLP pipelines
Microsoft Excel
Certifications
Data Science with Python
IBM
Data Analytics (Forage)
Deloitte
Data Visualization (Forage)
TATA
Excel Data Analysis
Coursera
Mock interviews on readyforhires
SQL & Databases (Beginner)Best 65%
45 questions answered on readyforhires in the past year, 1 active day, longest streak 1 day.
