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Data science graduate building practical skills

Master's student in Data Science, learning analysis, statistics, and machine learning while preparing for my first data role.

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Work samples

A selection of coursework and practice projects that show my approach to data cleaning, analysis, and model building while I complete my graduate program.

  • FitLife Studio No-Show Analysis
    FitLife Studio No-Show Analysis

    Data-driven requirements and process redesign • Diagnosed, in Excel, a 20.2% class-booking no-show rate across 110,522 real bookings; identified lead time as the primary driver (4.6% same-day vs. 33.0% at 30+ days) and a reminder-timing confound in the existing process. • Authored a BRD, stakeholder analysis, and an as-is/to-be process redesign; recommendation projected to recover roughly 210 booked spots a month. GitHub: github.com/Skybroapp/fitlife-no-show-analysis

    ExcelGitHub
  • Cathay Pacific Group
    Cathay Pacific Group

    Darden Business Strategy capstone • Diagnosed the erosion of Cathay's Hong Kong hub as Greater Bay Area airports (83.6M, 66.5M passengers) overtook HKIA's 61M; recommended redirecting its HK$150bn fleet investment toward premium/cargo over its loss-making short-haul unit (HK$996M loss, up from HK$204M), staged via existing order-book flexibility.

About me

Master's student in Data Science, learning analysis, statistics, and machine learning while preparing for my first data role.

I am Raffano Rajasa, a graduate student pursuing a Masters in Data Science. I have limited professional experience and am building foundational skills in data analysis, statistics, and machine learning as I prepare to start my career.

Externships

SQL & Database Architecture Externship with Breaking Games

In progress

Experience

Race Leader & Event Organizer

24-Hour Race · 2020

Co-Founder & Product Lead

SkyBro (Personal Project) · 2025 6 Present

English Language Tutor

In-Center & Online · 2021 6 2023

Education

Monash University, Indonesia

Master of Science in Data Science · Class of 2028

University of Maine at Presque Isle, USA

Bachelor of Arts in Business Administration · Class of 2026

YMCA of Hong Kong Christian College, Hong Kong

GCE A-Levels · Class of 2021

Skills

Data analysisStatistical modelingMachine learning basicsData cleaningPython
Back to work

FitLife Studio No-Show Analysis

Data-driven requirements and process redesign • Diagnosed, in Excel, a 20.2% class-booking no-show rate across 110,522 real bookings; identified lead time as the primary driver (4.6% same-day vs. 33.0% at 30+ days) and a reminder-timing confound in the existing process. • Authored a BRD, stakeholder analysis, and an as-is/to-be process redesign; recommendation projected to recover roughly 210 booked spots a month. GitHub: github.com/Skybroapp/fitlife-no-show-analysis

ExcelGitHub
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Back to work

Cathay Pacific Group

Darden Business Strategy capstone • Diagnosed the erosion of Cathay's Hong Kong hub as Greater Bay Area airports (83.6M, 66.5M passengers) overtook HKIA's 61M; recommended redirecting its HK$150bn fleet investment toward premium/cargo over its loss-making short-haul unit (HK$996M loss, up from HK$204M), staged via existing order-book flexibility.

View all work
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✅ Verified by Extern · ⏱️ In progress

SQL & Database Architecture Externship with Breaking Games

Turn six messy CSVs into an analytics database and a Q4 dashboard that drives real business decisions. SQL + Claude.

Analytics Database DesignData AnalysisSQL FundamentalsData Storytelling

Overview

The externship converted six CSV data sources into a structured analytics database and produced a Q4 dashboard. Work included inventorying the raw files, designing table schemas, and preparing queries for dashboard metrics.

SQL & Database Architecture Externship with Breaking Games

What I've accomplished

I documented all six data sources, wrote five SQL queries with returned results, sketched a dim_product table schema, and recorded three joins that connected traffic records to sales.

Project breakdown

I documented the six data sources, pasted five instant SQL answers, built a dim_product schema sketch, and added queries joining traffic to sales. The deliverable recorded queries, results, and short findings across weeks 1–3.

Google Docs
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I designed dim_product with a surrogate key, joined four journey tables via primary/foreign keys, built fact_product_performance, and produced a ranked reorder recommendation; I verified query results and traced mismatches in pageview joins.

Google Docs
Access

Situation: $37K in Meta ads and messy referral data. Task: connect spend to sales and produce a Q4 allocation plan. Action: cleaned referrals, built a channel taxonomy, calculated CTR/CPC/ROI per campaign. Result: a documented Holiday Game Plan with campaign-level ROI and specific keep/cut…

Google Docs
Access
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