Data Analyst

Hi, I'm Nawaf Alqurashi.

Certified Data Analyst with expertise in Power BI, SQL, Python, and Excel. Focused on uncovering insights, building impactful dashboards, and helping businesses make data-driven decisions.

View My Work ⬇ Download CV

About

Certified Data Analyst with credentials in CompTIA Data+ and Microsoft Power BI Data Analyst Associate. Experienced in data analytics, business intelligence, dashboard development, KPI monitoring, and reporting automation. Proficient in Power BI, SQL, and Excel, with a proven ability to deliver actionable insights that support operational and business decisions.

Holds a Bachelor's degree in Management Information Systems from King Abdulaziz University and completed the Data Science & AI Bootcamp at Saudi Digital Academy. Passionate about leveraging data to drive business value and continuous improvement.

Data Science Data Analyst Project Management Data Monitoring Model the Data Prepare the Data Visualize & Analyze the Data Manage & Secure Power BI Data Quality Characteristics Data Access & Governance Policies Dashboards Power BI DAX SQL Excel Python pandas polars Git & GitHub

Featured Projects

Data science, AI, and machine-learning projects solving real-world problems.

⭐
FUTURE STAR
Football Talent Prediction Platform
📋 WHAT IT DOES
Give it a young player's season stats, and it estimates the chance they'll become one of the best in their position next year — so academies can spot rising talent early and fairly.
⚙ WHAT IT LOOKS AT
Goals + assistsChance creation (xG)Passing & dribblingDefendingFair per positionHonest, no shortcuts
🧠 HOW IT WORKS
1 Clean & explore the player data
2 Caught a hidden flaw faking the accuracy
3 Learn from this season to predict next
4 Train & tune the model (XGBoost)
5 Ship it as a live web app
📊 RESULTS
0.75Accuracy
~2×Better than chance
~70%Talent caught
In plain terms: it reliably ranks who's most likely to break out — and its top picks are real young stars (Saka, Wirtz, Palmer, Musiala). ROC-AUC 0.75 · PR-AUC 0.36
🔭 WHAT'S NEXT
Sharper, better-calibrated confidence scores
Learn from more seasons & player growth
Bring it to the Saudi Pro League & academies
Refresh the model automatically each season
🎯 WHY IT MATTERS
Helps academies find young talent early, fairly, and without guesswork — supporting Saudi football development.
⚽ Spotting tomorrow's stars, today
★ Bootcamp Project · SDA × Le Wagon

Future Star

Football Talent Prediction Platform

An end-to-end ML system that predicts whether a young footballer (≤23) will become a top-20% performer in their position next season — built leakage-free so the score reflects real future potential, helping Saudi academies scout objectively.

🎯 Future Star probability from per-90 match stats
🕵️ Caught a target-leakage trap (fake 0.99) → honest ROC-AUC ≈ 0.75
📅 Temporal design: this season's stats predict next season's breakout
⚖️ Position-fair comparison (GK · DF · MF · FW)
🚀 Live interactive Streamlit app + FastAPI service
PythonXGBoostscikit-learnStreamlitFastAPI
▶ Live Demo ★ View on GitHub
Saudi Digital Academy × Le Wagon · Riyadh
★ GitHub Project

Customer Churn Prediction — Banking & Payments

An end-to-end churn model on 7,043 customers — identifying who's about to leave, why, and where a retention budget should go first. The whole analysis is framed in banking & payments language (autopay, commitment term, account age, lifetime value).

🎯 Scores every customer on churn risk × value
📊 ROC-AUC 0.85 — catches ~72% of churners (threshold-tuned)
💰 Surfaces ~$212K/month of revenue at risk → 4 action segments
Pythonpandasscikit-learnEDAClassification
★ View on GitHub
★ GitHub Project

Amazon Analysis: Pandas vs Polars

A comprehensive comparison of pandas and polars on a real-world Amazon dataset — exploring performance, syntax, and data-wrangling capabilities, scaled to 5 million rows for a fair test.

🧹 Cleans messy text columns into proper numeric features
⚙️ Fair benchmark on 5M rows across 5 operations
📈 polars runs 3–10× faster on sort & group-by
PythonPandasPolarsEDABenchmarking
★ View on GitHub
BI Dashboards Built with Power BI
Flights overview page
✈ Power BI · 2 Pages

King Khalid Airport — Flight Analysis

Flight Operations & Airline Performance · Oct 2024 – Sep 2025

150.5KTotal Flights
128Destinations
68Airlines
50.7%Departures
📈 Monthly Trend⏰ Peak Hours🌍 Global Map🏆 Top Airlines📊 Market Share
Key Insights
  • Saudia leads with 39.7% market share — the top 3 carriers (Saudia, flynas, flyadeal) handle 78% of all flights.
  • Peak hours are 18:00 – 22:00 (evening rush).
  • August had the highest monthly flight volume.
  • Arrivals and departures are nearly evenly split (49% / 51%).
  • Jeddah is the top route; only 0.07% of flights were cancelled.
Power BIPower QueryPivot TablesAviation
📂 Source: KaggleDataset →
Injuries overview page
🦺 Power BI · 2 Pages

Workplace Injuries — Saudi Arabia (Q4 2025)

Occupational Health & Safety Analysis · Ministry of HR · Q4 2025

9,947Total Injuries
86Fatalities
393Recovery w/ Disability
99%Private Sector
👥 By Gender🎂 By Age🌐 By Nationality👷 By Occupation⚠ Injury Cause
Key Insights
  • 9,947 injuries in Q4 — including 86 fatalities, and 99% in the private sector.
  • Top causes: mechanical forces 50.9% and falls 31.7%.
  • Construction is the most affected sector (3,101), then manufacturing (2,277).
  • 91% of injured workers are non-Saudi and 95% are male.
  • Injuries concentrate in ages 25–39; Eastern Region office reports the most.
Power BIPower QueryHSEArabic
📂 Source: Saudi Open Data PortalDataset →
PMO Analytics dashboard
📊 Power BI · Portfolio

PMO Analytics — Privatization Portfolio

Budget, Schedule & Risk across 174 projects · Q1 2026 · sample-enriched data

SAR 2.43BPlanned
174Projects
17Sectors
48.3%Utilization
🎯 KPIs⏳ Completion Gauge📌 Status Mix🏗 By Sector⚠ Risk
Key Insights
  • SAR 2.43B planned, 48% spent — only 3.4% of projects over budget.
  • Environment & Water dominates ~45% of the portfolio.
  • 119 projects (68%) carry medium-or-high risk; 26% high risk.
  • Average completion 46.5% — 88 On Track, 47 Delayed, 24 At Risk.
Power BIDAXPMO
📂 Source: Saudi Open Data Portal (NCP)GitHub →
Riyadh Hotels dashboard
🏨 Power BI · Python

Riyadh Hotels — Pricing & Value

Hotel Pricing & Booking-Channel Analysis · Dec 2024 – Feb 2025

55Hotels
1,275Avg Price (SAR)
4.23Avg Rating
18Sources
📈 Price Trend🆚 OTA vs Direct🗺 Map🏅 Top Hotels🏷 Price Tiers
Key Insights
  • The same hotel varies up to 93% by booking source.
  • Direct/brand sites cost ~2.1× the OTAs (1,886 vs 712 SAR).
  • Prices climbed +107% from December to February.
  • Price–rating correlation is weak (0.31) — pricier ≠ better.
Power BIPythonpandasDAX
📂 Source: KaggleGitHub →

Experience & Education

My professional journey.

Apr 2026 — Jun 2026 · Seasonal

Data Analyst — Team Supervisor | Technical Lead

Sela · صلة · Hajj Season
  • Supervised daily data analysis operations during the Hajj season, ensuring accurate and timely reporting of operational activities.
  • Developed and maintained Power BI dashboards to monitor pilgrim allocation, transportation progress, accommodation occupancy, and key Hajj performance indicators.
  • Monitored data quality and validated reports from multiple Hajj service providers to ensure accuracy and consistency.
  • Analyzed operational data and generated daily reports to support decision-making throughout the season.
  • Coordinated with Hajj service providers and internal stakeholders to collect, validate, and interpret operational data.
  • Guided team members in resolving data issues and meeting critical reporting deadlines during peak operations.
  • Delivered actionable insights and performance reports to management, enabling real-time monitoring of pilgrim services.
  • Managed high-volume datasets and ensured successful delivery of analytics under a fast-paced, high-pressure environment.
Aug 2025 — Nov 2025

Data Science & AI Bootcamp

Saudi Digital Academy

Intensive 9-week (480-hour) program focused on Python, Machine Learning, Deep Learning, and model deployment. Built and deployed ML applications with Streamlit and APIs, with hands-on experience in Docker and Google Cloud Platform (GCP).

2019 — 2024

Bachelor of Business Administration (BBA), Management Information Systems

King AbdulAziz University

Focused on information systems, data management, and business analytics.

Professional Certifications

Industry-recognized credentials in data analytics and BI.

CompTIA Data+ certificate
CompTIA

CompTIA Data+ (DA0-002)

Issued Feb 2026 · valid through Feb 2029

Verify →
Microsoft PL-300 certificate
Microsoft

Microsoft Certified: Power BI Data Analyst Associate (PL-300)

Earned Nov 2025 · Credential ID 4D72EBAA91A8C7AB

Data Science Bootcamp certificate
Saudi Digital Academy

Data Science & AI Bootcamp

Completed Nov 2025 · 480 hours

Microsoft Power BI Data Analyst certificate
Microsoft · Coursera

Microsoft Power BI Data Analyst — Professional Certificate

8 courses · Issued Nov 2025

Verify →
IBM Data Analyst certificate
IBM · Coursera

IBM Data Analyst — Professional Certificate

11 courses · Issued Apr 2025

Python for Data Science certificate
IBM · Coursera

Python for Data Science, AI & Development

Issued Jan 2025

Verify →

Get In Touch

Open to data analyst opportunities — let's talk.

✉ Email 📱 0552380130 in LinkedIn ⌥ GitHub ⬇ Download CV