Available immediately · Sydney + remote worldwide

Muntasir Md Nafis

Junior Data Analyst / Data Scientist · Sydney-based · Open to remote

I like the messy part: taking chaotic data and making it undeniable.

Graduate Temporary Visa (subclass 485) · Full unrestricted working rights in Australia

View Projects GitHub LinkedIn Contact Me

01 — About

Bridging code, statistics, and business decisions.

I started in Computer Science and fell in love with the stories hiding in raw numbers. A Master of Business Analytics at Macquarie taught me to bridge rigorous code and statistics with the clarity stakeholders need. Now I'm looking for junior Data Analyst, Data Scientist, or Business Analyst roles where I can build end-to-end pipelines, ship dashboards that get used, and implement machine learning models that drive real impact.

Master of Business Analytics

Macquarie University

Machine Learning

Classification · Forecasting

Data Visualisation

Power BI · Tableau

SQL & Analytics

End-to-end pipelines

02 — Skills

Tools, weighted by use

Grouped by how often I actually reach for each tool, not by category. What you see at the top is what shows up in nearly every project.

Daily driver

Reach for these every project — fluent without docs.

5/5

PythonSQLPandasNumPyScikit-learnMatplotlibJupyter NotebookGit & GitHubMicrosoft ExcelExploratory Data AnalysisData CleaningFeature Engineering

Comfortable

Strong working knowledge — used across multiple projects.

4/5

Power BITableauSeabornClassification ModelsRegression ModelsTime-Series ForecastingStatistical AnalysisModel EvaluationDashboard DevelopmentData StorytellingGoogle Colab

Familiar

Built with these in research projects — can ramp quickly.

3/5

TensorFlowPyTorchYOLOv5Detectron2MobileNetV3Deep LearningComputer Vision

03 — Education

Academic background

Master of Business Analytics

Macquarie University· North Ryde, NSW

Feb 2024 – Jan 2026

Achievements — 2nd Place — Business Analytics Capstone Project Competition (2025)

Bachelor of Science in Computer Science and Engineering

North South University· Dhaka, Bangladesh

Jan 2018 – Dec 2022

Achievements — Cum Laude Distinction

04 — Projects

Analytics, BI & machine learning work

Real-world projects across forecasting, predictive analytics, business intelligence dashboards, SQL, and applied machine learning research.

Featured Analytics Projects

Forecasting, predictive analytics, and exploratory business analysis.

03 projects

6 Years of Data

NEM Carbon Emissions Analytics (2019–2025)

PythonPandasTime-Series AnalysisData VisualisationMatplotlibCSIRO Emissions API

900+gCO₂/kWh peak detected in VIC evening windows

Analysed six years of Australian National Electricity Market carbon emission intensity data across NSW, VIC, QLD, SA, and TAS to identify high-emission peak periods, low-emission usage windows, and regional emission drivers.

5 Australian RegionsVIC 31% Emission Share900+ gCO₂/kWh PeakTime-Series AnalysisRegional Heatmaps

GitHub

3,000 Inventory Records

Dead Stock Prediction Using Machine Learning

PythonPandasNumPyScikit-learnMatplotlibJupyter Notebook

3,000inventory records modelled for stockout risk

Built an end-to-end predictive analytics workflow using 3,000 inventory records to identify products at risk of becoming dead stock across stock ageing, monthly demand, inventory turnover, ABC classification, and warehouse movement variables.

Logistic RegressionRandom ForestFeature EngineeringInventory Risk PredictionConfusion Matrix Evaluation

GitHub

99,461 Transactions

Dibs Retail Analysis (99K Transactions)

PythonPandasNumPyMatplotlibSeabornEDABusiness Analytics

99,461retail transactions analysed across 10 variables

Analysed 99,461 retail transactions across customer, product category, payment method, date, quantity, price, and shopping mall variables to identify revenue drivers, customer behaviour patterns, and marketing opportunities.

10 Variables5,024 Price Outliers Treated46.3M TL Highest Age-Group Spend49.9% Cash Payment ShareRetail Customer Analytics

GitHub

Dashboard & Business Intelligence Projects

SQL analytics, data modelling, and interactive dashboards.

03 projects

5 Years of Data

Victoria Road Crash Analytics Dashboard

TableauPythonPandasGeospatial Analysis

5 yrsof Victorian crash data mapped into one dashboard

Built a Tableau dashboard analysing 5 years of Victorian road crash records (2018–2023), visualising hotspots, severity trends, and risk factors for road safety analysis.

Tableau DashboardGeospatial AnalysisRoad Safety Insights

GitHub Tableau

SQL Analytics

Urban Eats SQL Analysis

SQLSQLiteDatabase DesignERD

Multi-tableSQL schema designed for café operations reporting

Designed relational database structures and wrote SQL queries to generate business insights and reporting for retail and café operations.

Database DesignBusiness ReportingData Modelling

GitHub

Power BI

Australian Population Trends Dashboard (Power BI)

Power BIDAXData ModellingETL

24.18Mpeople mapped across 20 years of ABS census data

Built Power BI dashboards using ABS census data (1996–2016) to analyse Australia's population growth, age structure, gender split, and country-of-birth diversity across all states and territories, supporting planning for infrastructure, healthcare, and education. Found Australia reached 24.18M total population with 8.28% growth, driven primarily by NSW, VIC, and QLD, with 91.11% Australian-born and strongest overseas-born shares from New Zealand and China.

24.18M PopulationABS Census 1996–2016Demographic Segmentation

GitHub

Machine Learning Projects

Applied machine learning, computer vision, and deep learning research.

02 projects

61,018 Records

Maternal & Neonatal Outcome Prediction

PythonScikit-learnPandasHealthcare Analytics

61,018birth records modelled across Kenya & Uganda

Predicted adverse maternal and neonatal birth outcomes using machine learning on 61,018 healthcare records from Kenya and Uganda. Compared multiple classification models including Random Forest, Decision Tree, KNN, and Logistic Regression to identify key risk factors and support data-driven healthcare decision making.

Random ForestHealthcare AnalyticsPredictive Modelling

GitHub

2,000 Records

Mobile Price Predictor

PythonScikit-learnLogistic RegressionKNN

97.25%accuracy predicting phone price tier (LogReg)

Built classification models on 2,000 mobile phone records with 20 hardware features (battery, RAM, camera, resolution, connectivity) to predict price range across 4 tiers — low, medium, high, very high. Compared Logistic Regression and K-Nearest Neighbors with grid search hyperparameter tuning, identifying RAM, battery power, and display resolution as the strongest price drivers.

LogReg 97.25%KNN K=11Scikit-learn

GitHub

Research Projects

Deep learning and computer vision research conducted with Masters research teams.

02 projects

Team · Computer Vision Engineer

YOLOv5

UAV Maize Tassel Detection

PythonPyTorchYOLOv5Detectron2Computer Vision

2 modelsbenchmarked on UAV maize imagery (YOLOv5 vs Detectron2)

Team research project applying deep learning object detection to UAV imagery for identifying maize tassels, supporting precision agriculture and aerial crop monitoring. Compared YOLOv5 and Detectron2 architectures to evaluate detection performance on agricultural drone footage.

Detectron2Computer VisionDeep Learning

GitHub

Team · Deep Learning Engineer

Medical Imaging

Tooth Decay Detection Using Deep Learning

PythonTensorFlowPyTorchMedical Imaging

4 modelscompared for dental decay detection from phone imagery

Team research project building computer vision models to detect tooth tissue destruction from smartphone microphotography, supporting automated dental diagnostics and early disease detection. Compared YOLOv5, Detectron2, FCOS, and MobileNetV3 architectures to identify the most effective approach for dental image analysis.

Deep LearningTensorFlowPyTorch

GitHub

Group & Collaborative Projects

Team-based business analytics and capstone projects, with my specific contributions highlighted on each card.

02 projects

Team · Customer Insights & Data Quality Lead

1.99M Records

LuminaTech Lighting — Customer Insights (BUSA8000)

1.99Msales records audited; 40.5% customer churn surfaced

Team business-analytics project for Macquarie's BUSA8000, analysing ~1.99M LuminaTech Lighting sales records across 2012–2013 to support customer retention, sales strategy, and operational decisions. Focused on data quality, customer base trends, churn behaviour, and EDA to underpin downstream statistical testing and predictive modelling by the team.

EDA & Data CleaningCustomer AnalyticsPython · Pandas

GitHub

Team · Task 1 Lead — Data Preparation & EDA

12K Listings

Used Car Price Prediction - Kaggle Competition

PythonPandasFeature EngineeringEDA

12K × 38used-car listings cleaned across 38 raw features

Team Kaggle competition predicting listed prices for ~12,000 used cars across 38 raw features (engine, drivetrain, dimensions, geography, listing metadata). The team trained and tuned regression models against a held-out leaderboard; my workstream owned Task 1 — turning the messy raw listings into a clean, model-ready dataset and surfacing the price drivers the modelling team built on.

38 FeaturesEDA & Feature EngineeringPython · Pandas

GitHub

05 — Experience

Work & research

Dispatch Team Member (Operations & Process)

WooliesX· Auburn, Australia

Jan 2026 — Present · Part-time

Analysed operational workflows, inventory validation processes, dispatch performance, issue resolution, and process efficiency within a highly automated customer fulfilment centre.

Research Assistant — Machine Learning & Computer Vision

North South University· Dhaka, Bangladesh

Jan 2023 — Dec 2023 · Full-time

Worked on dataset preparation, machine learning model training, and model evaluation for computer vision research using YOLOv5 and Detectron2, with a focus on object detection and research documentation.

06 — Contact

Let's build something with data.

Currently seeking Junior Data Analyst, Data Scientist, Business Analyst, Analytics Consultant, and Machine Learning opportunities across Australia and remote-first teams. The best way to reach me is by email or LinkedIn message.

md.nafis08@gmail.com

GitHub

github.com/nafis2508

linkedin.com/in/muntasir-md-nafis