Dr. Samuel Shamiri

📌 Professional Summary

Innovative and results-oriented Senior Data Scientist with a PhD in Statistics and over 15 years of experience in advanced statistical modeling, machine learning, large language models (LLMs), and cloud-based analytics. Proven ability to translate complex data into actionable insights for government, public policy, finance, and commercial sectors.

Deep expertise in NLP, generative AI, and Azure-based data science platforms. Track record of building and deploying scalable solutions using Python, R, Spark, Databricks, and MLflow.

🧰 Technical Proficiencies

Category Skills
Cloud Platforms Azure (ML, Databricks, Data Factory), Hadoop, Spark, Hive, AWS
LLM & Deep Learning BERT, T5, RNN (LSTM), CNN, GAN, RAG, Prompt Engineering, TensorFlow, PyTorch, MLflow
Machine Learning & Statistics Classification, Regression, Clustering, Forecasting, Anomaly Detection, Bayesian modelling, Bayesian Network, Monte Carlo Simulation
Languages & Tools Python, R, Scala, SQL, Git
Frameworks Hugging Face, MLOps, Docker, Spark-NLP

💼 Professional Experience

Senior Data Scientist | Jobs and Skills Australia (May 2018 – Present)

  • Successfully built and deployed an ensemble of machine learning models.
  • Deployed an NLP pipeline using Transformer models on Azure Databricks to analyse large, unstructured datasets.
  • Built system to match skills with qualifications.
  • Integrated MLflow to manage model lifecycle — reducing deployment time by 30%.
  • Advised on Azure-based scalable data infrastructure.
  • Mentored teams on ML, Python, and Spark.

Associate Director | Analytic Partners (Jan 2017 – Mar 2018)

  • Led ML initiatives; developed roadmap and increased client revenue by 15%.
  • Built market mix and digital attribution models — optimizing spend by over $5M.

Data Scientist & Senior Analyst | Equifax & Starcom (2012 – 2016)

  • Created credit risk models with XGBoost on Azure ML — boosting accuracy by 25%.
  • Designed automated Python/R/SQL workflows — increasing team productivity.
  • Delivered social network and econometric models for stakeholder intelligence.

Statistician | Forethought Market Research (2011 – 2012)

  • Led training on R for Marketing Science team.
  • Developed Hierarchical Bayes models (CBC, MaxDiff, MCMC, Gibbs).
  • Built GUIs in R for client-side solutions.

Senior Lecturer | University of Malaya (2009 – 2010)

  • Taught actuarial and financial math courses.
  • Supervised final-year actuarial projects and ran applied stats workshops.

🎓 Education

  • PhD in Statistics
  • Master in Financial Economics (Econometrics)
  • Degree in Statistics

🏅 Certifications & Publications

  • Machine Learning (Stanford / Coursera)
  • Apache Spark (MapR Technologies)
  • Published 10+ peer-reviewed articles on statistical modelling & financial risk
  • [Publication list available upon request]

🏆 Key Achievements

  • LLM Deployment: Reduced manual review by 50% via Azure BERT pipeline.
  • Azure Migration: Cut ML cost by 35% via Databricks refactor.
  • Award Finalist: ADMA 2014, Cross-Channel Analytics.
  • POEM Model: Developed unified MMM framework across continents.
  • Prophecy Method: Helped develop AMSRS-award-winning market model.