Daniel S.

Daniel S.

Python Developer

Australia
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About Me

Talented software engineer and data scientist with a varied background in software, hardware, and data analysis. Skilled in Python (including Tensorflow/Keras/Scikit-Learn), C, PCB Design, Ruby on Rails, Java, HTML, C#. Daniel is an emerging engineering professional with a Master of Engineering - MEng focused in Electrical with Business from the University of Melbourne. He has hands-on experience working with machine learning for the Melbourne property market, as well as using machine vision and deep learning to analyze data and form predictions for various client projects using OCR.

Work history

UpStack
UpStack
Python Developer
2020 - Present (4 years)
Remote
  • Create and develop innovative software solutions for different clients across a broad range of industries.

  • Participate in scrums consisting of cross-functional teams, both software and hardware.

  • Ensure that features are being delivered efficiently and on-time.

Systemize Consulting
Systemize Consulting
Software Consultant
2019 - Present (5 years)
Melbourne, Australia
  • Built and maintained a ResNet based object detector for a leading Australian Telecommunications company, used to assess if certain equipment has been installed and/or work been performed.

  • Developed a Docker based job processing system, for processing real-time and batch machine learning inference workloads, using CPU and NVIDIA GPUs on AmazonWeb Services and on bare-metal.

  • Built and maintained a text classifier using DistilBERT, to automatically classify line item expenses from invoices. Performed data analysis and data cleansing using Pandas and Numpy.

Secret Agent Property Services
Secret Agent Property Services
Data Scientist/Python Developer
2017 - 2019 (2 years)
Australia
  • Produced data driven reports and analysis about the Melbourne property market using machine learning algorithms and general data science techniques and methods.

  • Created a rolling quarter and property “score cards” displaying statistics and trends.

  • Worked on a report that investigated how a property's elevation above sea level influences its price, matching corresponding elevation data from Google Maps with prices.

WSP in Australia
WSP in Australia
Software Engineer Intern
2016 - 2018 (2 years)
Australia
  • Performed web app development in Python (Django) and JavaScript, including feature development, bug fixing, and documentation, for one of the world’s leading engineering professional services consulting firms.

  • Worked on multiple projects, such as the Macquarie Dictionary (MacMillan Publishing Australia) and Energy Rating Government Website.

  • Worked on the NSW FACS forms for the Australian Government.

GradReady Pty. Ltd
GradReady Pty. Ltd
Software Developer
2015 - 2016 (1 year)
Australia
  • Oversaw the architectural design and production of a new web service and site for GAMSAT, UMAT and High School (VCE and HSC) students.

  • Migrated the company from Google Apps for Business to Zimbra email, reducing email costs by more than 86%. Implemented various features within the site including: PayPal payments, Migration of data, Online Textbook and many others.

  • Managed Amazon Web Services for the company, including various EC2 instances, Elastic Beanstalk applications, Simple Emailing Service, Video Trans-coding Services, S3 and CloudFront.

Portfolio

Software Engineer - Enchanting Guess Game
Software Engineer - Enchanting Guess Game

Enchanting Guess Game - Building a game in Unity C# and implementing a custom shader with Microsoft Surface. This application is a very basic game, a version of the popular "Simon Says Game". There are three objects: a bowl, a metal cup, and a porcelain dish. Each object is clearly visible on a table in the middle of the scene and each object emits a different sound. A sequence of sounds (the sequence contains the sounds that are emitted by the objects) is played at the start of every round, and the user must input guesses for the sounds in the correct order to move on to the next level.

Software Engineer - WatermelonFlask
Software Engineer - WatermelonFlask

A simple flask app to upload an image and spectrometer data to automatically determine the ripeness of watermelon. The project was created using Python and HTML. Using a Hamamatsu Spectrometer, Raspberry Pi 3, Raspberry Pi Camera, and STM-Nucleo Microcontroller, the project determined the ripeness of specific watermelon varieties with 95% accuracy, using Keras and Tensorflow. Due to the success of the project I received a merit prize from the electrical & electronic engineering department.

Software Engineer - WatermelonUI
Software Engineer - WatermelonUI

Watermelon UI is a pyQT App for interfacing with Flask Server, logging spectrometer data, and capturing photos for a watermelon farm.

Software Engineer - Craigie Cattle Station
Software Engineer - Craigie Cattle Station

Craigie Cattle Station –LongeRange (LoRa) rain gauge, temperature & humidity remote monitoring. Using a Raspberry Pi 3 with an inAir9B Semtech 1276 LoRa Module as the base station and 9 Arduinos with inAir9B modules, and other parts. Based on Prof. Congduc Pham’s work.

Education

Master of Engineering (Electrical with Business)
Master of Engineering (Electrical with Business)
University of Melbourne
2017 - 2018 (1 year)
Bachelor of Science(Electrical Systems Major)
Bachelor of Science(Electrical Systems Major)
University of Melbourne
2013 - 2016 (3 years)