Rohinth Shanmugasundaram's Data Science Portfolio

Explore my skills, projects, and certifications in data science and analytics.

About

Welcome to my corner of the web! I'm a Business Intelligence Analyst bringing solid expertise in project management and data analytics.
Skilled in using tools like SQL, Python, and Power BI, I formulate data-driven business strategies and have demonstrated success through capstone projects, improving market share by 15% and analysing 12+ data sets during my MBA program.
I aim to showcase my work and capabilities, seeking a challenging role where I can expand my horizons across various functions.

Experience

Tiger Analytics - Data Science Intern

Conducted Exploratory Data analysis on structured datasets using Python (Pandas, NumPy), Identifying patterns and visualizing trends using Matplotlib, Seaborn, and Plotly to derive actionable insights.
Developed Linear Regression model (SKlearn, Statsmodel) filtering variables that have influence on the key variable of the dataset though R squared and P values.
Designed and automated interactive dashboards with Power BI and Tableau, incorporating KPIs, Maps, Trend lines, slicers, and dynamic data transformation

Statistical Models: Supervised Learning - Linear and logistical regression, decision trees, XG Boost, bootstrapping, unsupervised Learning Models – K Means, Hypothesis testing, univariate and multivariate testing, neural networks.
Statistical Tools: Scikit – learn, Statsmodel, SAS Enterprise Miner.
Programming Languages: SQL, Python, R Programming.
Data Manipulation Methods: NumPy, Pandas, Pivot Tables, VLOOKUP, HLOOKUP, XLOOKUP, Power Pivot.
Visualization Tools: Power BI (Power Query, DAX), Tableau.
Cloud Technology: Apache Spark, GCP.

Skills

Project Highlights

Explore my diverse data science projects and simulations here.

AB Testing (SQLite, Mode Analytics): Developed and analysed user engagement metrics, leading to key insights on customer behaviour.

Cyclist Data Analysis (R Program, Kaggle): Applied trend analysis to improve conversion of casual users into members for a bike-share program.

Distributed Computing(Apache Spark): Optimized Spark performance by 30% through partitioning, caching, and shuffle tuning while enabling time-travel queries.

Superstore Visualization (MS Power BI): Provided data-driven recommendations for expansion, targeting regional promotional strategies.

Project Portfolio

Exploratory Data Analysis (Python, Pandas, Seaborn): Identified top 3 states for expansion and best opening months (Dec/Aug/Mar/Nov) using sales/SGM trends, while highlighting high-risk store formats.

Linear Regression Model (Python, SKlearn): Found 'Total Store Sq. Ft', 'Centre Type Outlet', and 'Climate Hot' as top sales drivers, advising expansion focus while avoiding 'Centre Type Strip'

Coffee Orders (MS Excel): Analysed subscription patterns and provided strategies to boost brand popularity and standardize sales.

EDUCATION

Master of Business Administration (MBA) – Management Information Systems (MIS) - University of Toledo

Employed SAS for statistical modeling including regression, multivariate analysis, bootstrapping, clustering, decision trees, and neural networks, analyzing 12+ datasets as part of coursework. Developed strong foundations in business excellence, economics, finance, supply chain, and project management through 7+ real-world case studies. Graduated with a 3.56 GPA.

CAPSTONE BUSINESS STRATEGIC SIMULATIONS

Enhanced the market performance of a virtual company by conducting five rounds of strategic business process analysis across five product lines, leading to a 15% improvement in market share within a simulated environment.
Achieved this improvement by driving consumer preference analysis, product updates, and R&D investments, resulting in an 20% increase in product adoption and a 13% reduction in costs through automation enablement.

CERTIFICATION

Data Analyst Data Science– KGISL Micro College, (August 2025 – January 2026).
Google Data Analytics Specialization - Google & Coursera, (September 2022 – April 2023).
Distribution Computing with Spark SQL - University of California, (August 2023).
Data Wrangling, Analysis and AB Testing with SQL - University of California, (July 2023).
SQL For Data Science Specialization - University of California, (June 2023).
Power Bi A to Z Hands on Power Bi Training for Data Science – SuperDataScience Team, (Sep 2022).