Data Scientist

William Sloan

** ****** **, ***** ******** 043*-***-*** *********@*****.*** github.com/wjsloan TECHNICAL SKILLS

• In-depth knowledge of linear algebra, multivariable calculus, and statistics, and using these to solve complex problems in other fields

• Python experience, including the NumPy, Pandas, and scikit-learn packages

• Understanding of and ability to implement many machine learning algorithms

• Data wrangling and pre-processing techniques

• Natural language processing / text mining

• Querying databases using SQL

• Mathematical typesetting using LaTeX

• Communicating complex mathematical concepts and their significance to a general audience EDUCATION

Monash University - Bachelor of Science Advanced – Research (Honours), March 2015 – December 2018 Major in physics and mathematics, first-class honours in physics, 3.97 GPA ACADEMIC AWARDS AND SCHOLARSHIPS

2016 – Dean’s List Award

2016 – Monash Summer Research Scholarship

2017 – Monash Scholarship for Excellence

2018 – Dean’s List Award

2018 – J.L. William Scholarship

PERSONAL DATA SCIENCE PROJECTS

Full write-ups for these projects can be found on my Github page: github.com/wjsloan. Telecommunications customer retention

Using machine learning to identify customers of a telecommunications company who are likely to cancel their service, with 78% accuracy. The skills and processes involved were:

• Cleaning data to a consistent format appropriate for training a machine learning model

• Exploratory data analysis to determine features indicative of a high probability of service termination

• Implementing and evaluating different machine learning algorithms, including random forests Online review category and sentiment analysis

Building machine learning classifiers to determine the category and positivity of online product reviews. The category could be predicted with 94% accuracy, and the positivity classifier was 80% accurate. Skills involved:

• Implementing natural language processing techniques to convert text into an efficient, mathematical form

• Building machine learning models using the Naïve Bayes and logistic regression algorithms

• Implementing an ordinal classification algorithm as outlined in a research paper PHYSICS RESEARCH PROJECTS

Quantum car parking (Honours project, 2018)

Designing and testing an algorithm to find the optimal scheme for driving a quantum system between two states, with significant applications in the realisation of quantum computers. Some of the processes involved were:

• Writing code for a long and complicated algorithm, and using the results from its application to millions of randomly generated states to evaluate its performance according to several different metrics

• Using the results of contemporary research papers to guide the investigation

• Communicating the details and significance of the research to a general scientific audience in two presentations, as well as writing the results and comprehensive background theory in a thesis Entanglement-producing quantum maps (Third year project, 2017) Investigating how to establish quantum entanglement between two particles using a certain communication protocol, which could allow us to design an “engine” to create entangled particles. Skills and processes involved:

• Simulating a quantum communication protocol in Python, involving complex linear algebraic operations

• Using the NumPy and Pandas modules to efficiently generate, save, and analyse results from hundreds of thousands of simulations, in an effort to optimise our theoretical entanglement engine

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