Data Quality Scientist

Overview

The Data Quality Scientist supports instruments that are deployed worldwide by offering assistance to both internal teams and external clients. They answer questions, identify root causes, debug incidents, and put fixes into action. Although there are minimal travel requirements for this desktop support employment, it does include working on a roster during predetermined shifts, which may include weekends. In order to maintain communication with other team members, Chrysos worldwide uses a hybrid work style that requires team members to show up to the office three days a week during critical hours.

Responsibilities

• Provide office-based oversight and assistance for the installation and testing of PhotonAssayTM instrument detectors. • Analyze PhotonAssayTM instruments remotely to make sure that availability, accuracy, and overall performance goals of the client are met or surpassed. • Answer clients' and stakeholders' inquiries in a timely and correct manner. This includes analyzing reports, returning emails and phone calls, and outlining how to fix technical problems. • As needed, offer helpful support with the commissioning and setup of new instruments. • Organize and conduct regularly scheduled meetings with clients and stakeholders. • Create instructional and training resources. • Engage with employees and clients locally and internationally to assist both anticipated and unforeseen occurrences.

Requirements

• A STEM degree from a college or university (preference given to math and science) or comparable work experience • Experience with data/information analysis and reporting • Experience in a technical support capacity • Outstanding written and verbal communication abilities; strong interpersonal skills, especially the ability to collaborate across several technical disciplines. • Capacity to operate in a global team setting • Capacity to tackle problems methodically • Citizenship or permanent residence (or working privileges) • Expertise carrying out quality control in a lab setting • Experience analyzing data or statistics in a commercial or laboratory setting • Familiarity with basic programming, charting, and scripting languages such Power BI, Python, R, or comparable • Knowledge of software and/or information technology • Familiarity with using instruments like oscilloscopes, signal generators, and multimeters for basic electronics testing and troubleshooting. • Knowledge of the productivity software suite Microsoft Office