Josh Amoils
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Josh Amoils Email & Phone Number

Team Lead - Signal Intelligence Operations at DroneShield
Location: Sydney, New South Wales, Australia 10 work roles 4 schools
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Current company
Role
Team Lead - Signal Intelligence Operations
Location
Sydney, New South Wales, Australia
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Who is Josh Amoils? Overview

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Josh Amoils is listed as Team Lead - Signal Intelligence Operations at DroneShield, a with 293 employees, based in Sydney, New South Wales, Australia. AeroLeads shows a matched LinkedIn profile for Josh Amoils.

Josh Amoils previously worked as Machine Learning Engineer at Droneshield and Data Engineer at Droneshield. Josh Amoils holds Bachelor'S Of Data Science And Decisions (Computational Data Science) from Unsw.

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DroneShield

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About Josh Amoils

Josh Amoils is a Team Lead - Signal Intelligence Operations at DroneShield. Colleagues describe him as "There are a few people I am dedicated to writing a recommendation for, and Josh is one of these. I had the luck of working with Josh on multiple occasions: the first time we met was during a Data Science competition held by RelevanceAI. He led his team to victory, dominating against six other competing groups. Since then, we kept in touch, sharing the chance to work on other work-related projects. During the years, I saw him diligently become an expert in the field while developing a unique understanding of multimodal embeddings, a feature that I noticed while he was deploying a scalable stack for an art startup, Cohart, by himself. In addition, he is dedicated to expanding his knowledge way beyond data science: I witnessed him interacting with clients, negotiating, and closing contracts with no external help. I am more than happy to write this recommendation for such a skilled Engineer." and "Josh worked as an intern at American Express reporting into myself in the commercial risk management team. Upon starting the role, he immediately brought an enthusiasm and passion to wanting to learn. He quickly picked up and began mastering his technical skills - mostly using python and sql languages. He is an excellent communicator and has the ability to explain complex items/data in a simple manner. Josh will be an excellent candidate for future employers and has the ability to work in many diverse areas. All the best to him for his future endeavours."

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DroneShield
Droneshield
Team Lead - Signal Intelligence Operations
Sydney, NSW, AU
Website
Employees
293
AeroLeads page
10 roles

Josh Amoils work experience

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Team Lead - Signal Intelligence Operations

Sydney, Nsw, Au

Machine Learning Engineer

Current
Sep 2024 - Present

Data Engineer

Sydney, New South Wales, Australia

Jan 2024 - Aug 2024

Data Scientist

Utrecht, Netherlands

- Clinical AI 1: Built a world-first cry detection system for nurses to better attend to newborns in the neonatal intensive care unit in collaboration with clinical stakeholders. Single-handedly improved the AI component (a CNN trained on audio spectograms) from a TRL 4 (50% precision) to a TRL 8 (96% precision, 97% recall). Built an additional codebase to scalably ingest training data from the hospital (over 1TB) and annotate training data 5x faster.- Clinical AI 2: Developed an experimental AI pipeline that performs automated General Movement Assessment (used to assess cognitive development) of a newborn baby via video recording. Involved pose estimation models (e.g. OpenPose and Google's MediaPipe), creating an API endpoint and deployment using Docker and AWS Lambda.- Gap Selling: Built a sales funnel to sell research licenses of Neolook software, resulting in 2 paid opportunities. - Product Management: Designed/Built a ICU data solution from ideation to validation with clinicians. In addition, built performance reports and visualised user feedback. - Medical Device Regulation (MDR): Researched/Prepared regulatory filings to CE-mark Neolook's products in accordance with EU MDR software-as-a-medical device rules and relevant ISO standards.

Dec 2022 - Nov 2023

Data Engineer (Research Assistant)

- Big Data Wrangling: Built pipelines to process netCDF model output from 34 global & regional climate model simulations for analysis by world-leading climate scientists. The dataset is in the process of being published. - Climate Research: Wrote a research paper on the statistical influence of regional down-scaling schemes on how global climate models resolve extreme precipitation over time (supervisor Prof. Lisa Alexander). - Stats \& Data Visualisation: Programmed complex climate algorithms for use in UNSW course CLIM3001 tutorials.

Sep 2021 - Aug 2022

Data Scientist

- Computer Vision Development: Built an digital artwork recommender system using OpenAi's CLIP model for image encoding and KNN for inferencing a vector database of encoded images stored on Relevance AI. - Cloud Deployment: Hosted the entire pipeline on AWS using S3, Lambda and API Gateway.

May 2022 - Jun 2022

Credit Risk Intern (Unsw Co-Op)

Sydney, New South Wales, Australia

- Risk Strategy: Designed a limit increase initiative projected to make $Xm+ in additional revenue for AMEX.- Big Data & Analytics: Automated interactive monthly risk reports saving 2 days of manual work, built a widely used Excel bank statement scraper to easily monitor accounts and decisioned 20+ credit limit escalations.- Thought Leadership: Convinced my risk team to incorporate a customer's expected profitability - not only their risk of default - into credit limit calculations.

Feb 2021 - Aug 2021

Undergraduate Research Scholar

Sydney, New South Wales, Australia

In this 6-week summer scholarship I worked at the Climate Change Research Centre UNSW under Prof. Lisa Alexander and Dr Margot Bador comparing how state-of-the-art dynamical climate models scale one specific measure of extreme rainfall into the future. This was an amazing opportunity to self-learn a range of technical skills while undertaking original climate research. Achievements:- Obtained rigorous experience managing climate data (netCDF files), extracting the desired climate indices and generating geo-spatial plots (using specialised Python libraries). This was my first interaction with genuinely BIG data; the files are churned out by supercomputers that simulate the entire planet's climate every 30mins for hundreds of years!- Wrote shell scripts to automate the file management and production of plots. - Having finished the 6-weeks worth of work in 3-weeks, the scope of my work was extended to compare how the extreme rainfall index (rx1day) scaled across land/sea and seasons. - Wrote a 12-page scientific report on my research and findings. Problem Overview:"While global climate models (GCMs) remain our best tool for investigating the Earth’s system response to anthropogenic forcings, their spatial resolution (generally hundreds of km) is much coarser than the scales of the key processes leading to precipitation extremes (e.g. intense convective rainfall events). Therefore, parametrizations are necessary and the simulation of precipitation is not explicitly resolved in models. Spatial resolution is finer in regional climate models (RCMs) (generally tens of km), which is expected to improve the simulation of precipitation extremes that are very sensitive to spatial contrasts and topography.How the output of global and regional models scale with respect to the other is rarely compared. In particular, it is unclear how the future changes in precipitation extremes from large ensembles of regional climate models compare to those from global models."

Jan 2021 - Feb 2021

After-School Tutor

Sydney, Australia

- Co-founded a tutoring program designed for students with special learning needs.- Facilitated the personalised learning of 15+ students weekly.

Feb 2019 - Dec 2020

Data Analytics Intern

Sydney, Australia

- Used data scraping (Selenium) to build the first search engine for provider services using NDIS taxonomy.- Researched potential investors and introduced the seed round’s lead investor to Provider Choice's founders.- Tracked operational efficiency of invoice processing and implemented processes to improve processing efficiency by ~60%.- Market Analysis: Generated 24 capability documents on competitors and a set of indicators to determine their performance.- Acquired customer service skills by resolving customer complaints.

Mar 2019 - Jul 2019
Team & coworkers

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4 education records

Josh Amoils education

Bachelor'S Of Data Science And Decisions (Computational Data Science)

Atlassian x DataSoc Datathon | Project Leader | 1st Overall Relevance Ai x DataSoc Social Impact Challenge | Project Leader | 1st Place.

Education record

Activities and Societies: School prefect, Swimming Age Champion throughout high school (incl. district champion), Triathlete, Orchestra.

FAQ

Frequently asked questions about Josh Amoils

Quick answers generated from the profile data available on this page.

What company does Josh Amoils work for?

Josh Amoils works for DroneShield.

What is Josh Amoils's role at DroneShield?

Josh Amoils is listed as Team Lead - Signal Intelligence Operations at DroneShield.

Where is Josh Amoils based?

Josh Amoils is based in Sydney, New South Wales, Australia while working with DroneShield.

What companies has Josh Amoils worked for?

Josh Amoils has worked for Droneshield, Neolook Solutions, Unsw Climate Change Research Centre, Cohart, and American Express.

Who are Josh Amoils's colleagues at DroneShield?

Josh Amoils's colleagues at DroneShield include Megan Bain, Sarah Walmsley, Jorden Ong, Norman Oliveria, and Sunil Taneja.

How can I contact Josh Amoils?

You can use AeroLeads to view verified contact signals for Josh Amoils at DroneShield, including work email, phone, and LinkedIn data when available.

What schools did Josh Amoils attend?

Josh Amoils holds Bachelor'S Of Data Science And Decisions (Computational Data Science) from Unsw.

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