Rohinth Shanmugasundaram's Data Science Portfolio

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

• Quantitative Methods: Statistical Modeling – Linear and logistical regression, Hypothesis testing, univariate and multivariate testing, clustering, decision trees, bootstrapping, neural networks, Prompting.

• Statistical Tools: SAS Enterprise Miner, NumPy, Pandas, Scikit – learn.

• Cloud Technology: Apache Spark, GCP.

• Visualization Tools: Power BI (Power Query, DAX), Tableau, Pyplot, Seaborn Matplotlib.

• Programming Languages: SQL, Python, R Programming

• Data Manipulation Methods: VLOOKUP, HLOOKUP, XLOOKUP, Pivot Tables, Power Pivot.

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.

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)

• Employed SAS for Statistical Modelling, incorporating regression and multivariate analysis, bootstrap for random re-sampling, clustering for segmentation, decision tree for model comparison, and employing neural networks for machine learning tasks. Analyzed 12+ data sets as part of coursework.

• Gained expertise in business excellence concepts, business objectives, economics, financial and accounting fundamentals, supply chain management, computer science, project management, IT, and technical business relevance. Applied these principles to 7+ real-world business case studies.

• Wrapped up the course with excellence, proudly secured a noteworthy 3.56 GPA in entirety.

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

1. Google Data Analytics Specialization - Google & Coursera

2. Distribution Computing with Spark SQL - University of California, Davis

3. Data Wrangling, Analysis and AB Testing with SQL - University of California, Davis

4. SQL For Data Science Specialization - University of California, Davis

5. Power Bi Workshop - Growth School

6. Power Bi A to Z, Hands on Power Bi Training for Data Science - SuperDataScience Team