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QA Manager
2 weeks ago
About Us
Arpalus is a game-changer in the retail market, providing a simple, powerful and accurate way for brands and retailers to collect, measure and analyze important data from physical shelves in real-time through a smartphone app. We provide an online dashboard with real-time reporting on a SKU-level, backed by insights and analytics, enabling managers to make decisions with confidence.
Job Description
As a QA Manager, you will play a crucial role in leading the quality assurance efforts of our product. You will be responsible for end-to-end testing, which includes testing our app, computer vision models/training data and Power BI dashboard. You will work closely with our Data Science and Engineering teams to ensure that the full product cycle is thoroughly tested and meets our quality standards.
Responsibilities
- Spend time at retailer stores where our clients use the mobile app in order to execute complex QA actions
- Create a steady QA report process per domain per project
- Create and lead the implementation of a comprehensive QA process
- Identify and report issues or inconsistencies in data annotations and training to the Data Science and Engineering teams
- Test and implement a QA process for the data in the Power BI dashboard
- Complete tasks within specified deadlines and meet productivity targets
- Lead and workwith Agile work processes
Requirements
*Qualifications:*
- Bachelor's degree in Computer Science, Engineering, or related technical field (Master's degree preferred).
- Proven experience (5 years) in software quality assurance, with a focus on computer vision, machine learning, or related technologies within the retail industry.
- Strong leadership skills with experience in leading and managing QA teams.
- Solid understanding of computer vision concepts, algorithms, and deep learning models.
- Proficiency in programming languages such as Python, Java, or similar languages used in test automation.
- Experience with testing frameworks, tools, and methodologies related to computer vision and machine learning.
- Excellent problem-solving abilities, attention to detail, and strong analytical skills.
- Effective communication skills with the ability to collaborate across multidisciplinary teams and articulate complex technical concepts to non-technical stakeholders.
- Hands-on experience in implementation and management of Agile work processes
