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A highly competent data scientist with three years experience developing and implementing data analysis and modelling processes in a startup business.
My key strengths lie in my ability to apply machine learning and statistical methods to find meaningful insights in data, and create practical models to solve real world challenges in golf.
I am looking for the opportunity to expand my experience of using cutting edge technology and techniques in sports prediction.
- Sports Betting/Trading
- Probabilistic Modelling
- Machine Learning Models
- Scikit Learn
- Data Visualisation
- Analysis of golf market and performance data to produce probabilistic estimates of tournament winner
- Live and pre event trading on Betfair exchange
- Development and enhancement of models to analyse player performance and predict future performance
- Live brokerage requests for golf
Senior Data Scientist
- Working to implement data analytics across the world of golf, including with professional players, European Ryder Cup team, and across media outlets
- Ingesting and managing a variety of data sources into a central database
- Developing and implementing machine learning models to assess past performance and predict future results
- Extract actionable insights from data and communicate using appropriate data visualisation
- Leading constant improvement across our data stack
- Monitoring and managing real time risk
- Live updating of sports odds to reflect liability and updates
- Regular reporting on trading financial outcomes and associated risk elements
- Proactively created and implemented a number of processes to automate previously manual odds creation across the business
- 3 roles within construction companies
- Top graduate into the Sisk Graduate Programme in 2014
- Role immediately involved high levels of responsibility, accuracy and diligence
- Management of technical areas such as layout and quality checks across various construction areas
- Dealing with large teams of site specialist workers, ensuring close collaboration and alignment
- Made the decision to leave the construction industry to pursue a more technically challenging career in data science
B.Eng Energy Systems Engineering
- 2.1 Result
- Covered a broad variety of topics including introductions to multiple programming languages (Python, C++, Matlab, Fortran, Octave)
- Excellent mathematical foundation which allowed me to transition into a data science career with minimal supplementary study in this area
Stock Price Prediction
Use the Sentiment Analysis Algorithms to understand the stock sentiments.
Project: Twitter Sentiment Analysis
Tools: NLTK, Python
Algorithms: Sentiment Analysis
Stock Recommender Systems
Recommender systems have become the most popular feature of the stock market. We have developed a artificial intelegint stock recommender tool using the Deep Neural Networks and classification algorithms
Tools: Python, sklearn
Algorithms: Deep Neural Networks, classification algorithms
Customer Support System
Customer support has become a challenging job for every business. We build a “customer support system” to address and support the needs of the customers.
Tools: OpenCV, Python
Algorithms: Convolution Neural Network and other facial detection algorithms