What are the responsibilities and job description for the QA Data Scientist position at NavTrac?
**Overview**
NavTrac is a quickly growing VC-backed company that brings computer vision AI technology to supply chain management, seeking a technology leader to help deploy and scale our computing infrastructure (cloud and edge). The majority of the work is in the Data Science for Quality Assurance setting, with a significant data processing and monitoring component. Therefore, we seek strong programming experience in Python, SQL, Postman, among other modern Data Science technologies.
**Work Culture Expectations**
- High standards in development process: code quality, maintainability, and readability
- Keen attention to detail
- Great communication skills: effective listening and speaking
- Experience writing clear, concise, and detailed specifications
- Ability to work remote-first in an early stage company with many interesting challenges
**Professional Skills**
- Computer Science education background (Bachelor degree or higher; Master’s preferred)
- Programming: Python, SQL
- Data science experience or interest is a major bonus
- Fluent in modern command-line interfaces and tools
- Experience with Agile development environments
- Keen attention to detail, especially when processing large quantities of data
- Experience with modern Quality Assurance principles and best practices
**Responsibilities**
- Own end-to-end testing and evaluation of a range of web applications, both customer facing and internal
- Develop and maintain new processes for reviewing large amounts of data, verifying expected patterns and detecting anomalies
- Mine and analyze data from internal ground truth annotation tools/customer databases to drive optimization and improvement of product development and business strategies
- Assess the effectiveness and accuracy of new data sources and data gathering techniques
- Develop custom data models and algorithms to apply to data sets
- Use predictive modeling to increase and optimize customer experiences, revenue generation and other business outcomes
- Regularly communicating with the stakeholders and the development team to identify the features and the metrics for data accuracy processes
- Manage the development of the tooling needed for the quality assurance and data accuracy work from the product point of view.