I am a business-minded and highly motivated data scientist with 9 years of experience creating data-driven solutions throughout the Oil & Gas, Manufacturing, and Telecom industries. I have strong communication skills with the ability to acquire buy-in from the top level non-technical stakeholders across the organization and deliver impactful results to the business.
In the past 10 years, I have moved from the world of wireless communications to commodity price tracking and data science in the Europe and Middle East. It turns out that deep knowledge of stochastic processes, probability and statistics can help a lot in predicting and analysing commodity prices. This led me to have a current interest in data science, machine learning, time series analysis, and deep learning. Having started out with MATLAB, I am comfortable with Python data sicnece and statistics libraries used in web scraping, EDA, visualisation, data cleaning, and ML. I am also familiar with SQL and spark, as well as Montecarlo simulations and numerical analysis. Apart from technical skills, I have extensive business experience with is the result of working across Telecommunication, Manufacturing and Oil and Gas sectors handling a variety of optimisation and data related roles.
I have a PhD in Electrical Engineering from The University of Auckland, New Zealand. I have an extensive background in stochastic processes, probability and statistics, chaos-based wireless communication and physical layer security.
All of projects below are deployed on cloud based solution. As you can see I manage all my projects through the full ML cycle, from data sourcing to deployment.
- 1 End-to-End Customer Churn Prediction Project in Azure
- 2 Consumer Price Index Predictin Using Time Series Techniques
- 3 Champions League Soccer Match Prediction
- 4 Exploratory Data Analysis on Gas Pipieline Incidents
- 5 Dataquest Projects
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