Position: Python Automation QA Engineer (healthcare project)
Company: Symphony Solutions
Experience required: 2y
English level: upper

**Customer description:**
**ScreenPoint** is a leading company that develops and markets breast image analysis and cutting-edge machine learning applications and services. Our product Transpara aims at improving breast cancer survival rates by detecting cancers earlier so that treatment can be more effective and less invasive.

**Project description:**
ScreenPoint is looking for an enthusiastic and skilled automation test engineer for our medical software devices. You’ll be part of a highly motivated and collaborative group of experts in breast imaging, artificial intelligence, algorithm development, and clinical research who work closely together in an informal atmosphere.

**Requirements:**
- 2+ years of software testing and automation;
- Experience in QA Automation using Python;
- Understanding of OOP;
- Hands-on experience with both white box and black box testing
- Evaluating forms and processes for software testing and methodology, including writing and execution of test plans, debugging, and testing scripts and tools.
- Experience in writing clear, concise, and comprehensive test plans and test cases
- Experience with design and integration of software running on multiple platform types.
- Experience with Linux
- Experience working in an Agile environment;
- Upper-Intermediate level of English.

**It will be a plus:**
- Automation experience with Robot Framework

**Responsibilities**
In this position, you will contribute to further optimizing and improving our testing activities to help us bring our latest developed technology soon to clinical practice. 
This includes a lot of creative thinking and hands-on work:
- Design and implement the automated test pipeline and environment.
- Be the first with hands-on experience in our latest developments by executing both manual and automated tests.
- Help to quickly bring new versions of an innovative solution to improve breast cancer screening worldwide to clinical practice
- Interaction with all the relevant stakeholders, including experts on clinical, quality, AI, and software engineers, to define the required tests and testing strategies.