aadam gafar — data scientist

Building tools for people who hate wasting time.

I believe the best software is felt, not seen, whether it’s an equity forecasting framework or a focused YouTube UI. I build tools that are lean, efficient, and intentionally invisible.

github ↗ linkedin ↗

about

Data scientist and software engineer with 3+ years of experience, advanced training in machine learning and AI from the University of Cambridge, and a self-directed background in statistical modelling and time series forecasting. I've combined strong mathematical foundations (BSc Physics) with practical engineering skills to build end-to-end data pipelines and predictive models. Experienced in Python, SQL, scikit-learn, XGBoost, and statistical modelling frameworks. Seeking a data science or data engineering role where rigorous methodology and production-grade code quality are both valued.

Currently open to data science, data engineering, and ML engineering roles. Get in touch at aadamhgafar@gmail.com or via LinkedIn ↗.

projects

education

Career Accelerator in Data Science with Machine Learning & AI University of Cambridge ICE · 2025 - 2026
  • Advanced curriculum covering statistical modelling, supervised and unsupervised ML pipelines, deep learning, and Python-based model development and evaluation.
  • Coursework emphasis on rigorous methodology, cross-validation, and real-world deployment - directly informing the forecasting framework project.
BSc Physics — Pass with Merit University of Glasgow · 2018 - 2021
  • Applied advanced calculus, linear algebra, probability theory, and statistical inference to complex physical datasets.
  • Developed strong mathematical foundations in error analysis, computational modelling, and scientific reasoning that underpin current data science practice.

experience

Software Developer Totalmobile Ltd · 2023 - Present
  • Optimised backend data processing and SQL logic for large-scale datasets, improving query throughput and pipeline reliability in a production environment.
  • Engineered automated data validation protocols for RESTful APIs ensuring high data integrity across downstream consumers.
  • Collaborated in an agile engineering team, contributing to code reviews, sprint planning, and production deployments.
Software Developer Culina Group · 2022 - 2023
  • Designed and deployed ETL pipelines in T-SQL to migrate and normalise logistics data across platforms, improving data quality and accessibility for analytical use.
Data & Analytics Intern Capita plc · 2022
  • Developed foundational data engineering pipelines and applied machine learning techniques in Python to solve business-centric data problems across large enterprise datasets.

skills

languages & libraries

Python (pandas, NumPy, scikit-learn, statsmodels, XGBoost, Plotly, ruptures), SQL (T-SQL, PostgreSQL)

machine learning & statistics

Time Series Forecasting (SARIMA, SARIMAX, Walk-Forward Validation), Change Point Detection, Stationarity Testing (ADF, KPSS), Information Criteria (AIC/BIC), Ensemble Methods

product & ui/ux

Product & UX: CSS Architecture, Extension Development, UI/UX Design, Performance Optimization

data engineering & tools

ETL Pipeline Design, RESTful API Integration, Data Validation, Git, Postman, Chrome/Firefox DevTools

tools & platforms

Git, Jupyter, Google Colab, VS Code, Postman, HuggingFace Hub

mathematical foundations

Linear Algebra, Statistical Inference, Probability Theory, Hypothesis Testing (Ljung-Box, Shapiro-Wilk)

contact

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