Volunteer Python Quality Assurance Engineer
Interested in applying your development skills to help in this and future pandemics?
We are a non-profit organization looking for a Volunteer Python Quality Assurance Engineer to join our team and help us develop our product for the global good. We are developing a new, flexible, sophisticated but easy-to-use object-oriented holistic framework for modeling infectious disease risk, transmission & spread, along with a web app. We have a >30,000 line Python code base with many unit tests, but we have a backlog of QA & tests that are needed. Going forward, you will be essential in keeping our Test-Driven Development (TDD) on track. We have multiple areas in which QA is needed, and you may specialize in one or more of those:
- Mathematical/Numerical Modeling & Statistical Methods for Public Health/Epidemiology
- Machine Learning / Probabilistic Programming
- Web User Interface & API
- Database & Data processing
- Framework Core classes
- API Security
Responsibilities
You will apply your expertise in Python to improve upon our code:
- Reviewing implementation & test code & documentation
- Refactoring existing code (potentially)
- Testing: Automated (writing, verifying & running unit & integration tests) & Manual
- Assuring good test coverage
- Writing/Updating code documentation
- Coordinating with others
- Documenting issues clearly
Requirements
Experience as a Python Developer and/or Test/QA engineer (preferably of frameworks)
Strong knowledge of Python (versions 3.8-3.10), including most language features, such as:
- MetaClasses
- Decorators (all types) & Context Managers
- Proxy Classes
- Generators (including Asynchronous)
- Multithreading & multiprocessing
- Standard library, especially unittest
Know how to write a Mock
Proficient with Git
Knowledge of Torch or NumPy and numerical modeling & analysis
Data Science and/or User Interface (UI) development/testing experience preferred,
including UI testing with selenium
Pyro or other probabilistic programming language (PPL) knowledge a plus
Public health, epidemiology, medical or statistics & scientific knowledge (strongly preferred)
Database development experience preferred
Knowledge of reStructuredText and SymPy preferred
Familiarity with Docker a plus
Ability to follow a high-paced Agile, test-driven development process, working on a small team
Adaptable
Reliable
Team spirit
Good problem-solving skills
Willingness to be involved in and commit to a volunteer assignment
Location
Fully remote
About Quantum Risk Analytics, Inc.
We are a 501(c)(3) federally-tax-exempt charitable non-profit research organization founded by MIT alumni.
Our mission: To help mitigate the COVID-19 pandemic and future epidemics by developing and deploying robust risk assessment tools that predicts real-world infection, long-COVID, severe disease and mortality risk, thus empowering individuals, groups, and organizations to make better risk-informed decisions about their activities. Our larger mission is to address emergencies with analytics, and we will be branching out into other domains in the future.
Pandemonium is a COVID-19 Risk Assessment & Projection Model being developed by Quantum Risk Analytics, Inc. as its first product.
The basic framework of the model will allow for an arbitrary degree of demographic and spatial refinement where data is available as well as allow various submodels to be incorporated into the overall model making this a very extensive and extensible framework that can be used by researchers and others. (For more about our model design, please refer to the draft proposal on our website.)
Some key technical attributes of our model framework so far:
Stochastic (draws are made from probability distributions, giving distributions as model results and thus statistical metrics such as confidence intervals)
Regional & Compartmental (each region’s population is categorized into distinct compartments, the evolution of which is modeled)
Individualized (allows specified individuals to be modeled in conjunction with the larger epidemiological model)
Heterogeneous (epidemiological parameters can vary over time and region)
Spatially-Hierarchical (smaller regions within larger regions can be modeled where data is available for greater refinement and specificity)
Dynamic (allowing for specific travel history/plans & commuting pattern changes over time)
Demographically-structured (differences among demographic groups based on age, race, etc., can also be modeled where there is data available)
Incorporates micro mechanistic submodeling (models the physical mechanics of transmission in micro scenarios, fully integrated with the epidemiological model)
Incorporates vaccinations (the effectiveness of vaccines as provided by submodels are utilized).
Modular (allows for various submodels to be developed that are narrow in scope but still benefit from being connected to the larger framework and its other submodels, epidemiological model and inference capabilities)
Machine Learning built on the Pyro Probabilistic Programming Language (PPL), using Markov Chain Monte Carlo (MCMC) and other statistical inference techniques. (This allows the strongest inference practical from imperfect, missing and limited data, and forecasts into the future.)
We continue to develop this model to include additional features, information & detail. We plan to make our model framework open-source around the same time that we launch our risk assessment app for general use.
Quantum Risk Analytics, Inc. is a 501(c)(3) non-profit organization founded by MIT alumni, bringing together talented, motivated people from different countries and with diverse backgrounds. This has been an all-volunteer effort with volunteers from 3 continents. We want to contribute our skills for the greatest good of the world, devastated by the COVID-19 pandemic. We want to help as many people as possible, including and especially the more marginalized, both in the US and around the world. This is why we wish to make the service available to everyone for free and why Quantum Risk Analytics, Inc. is a non-profit organization. If you have the interest, commitment, and ability to contribute your skills while you gain experience and knowledge working on a real-world product, please apply!
How to Apply
Please, E-mail us with your resume and a brief cover letter.