Data Metrics Analyst

As a Data Metrics Analyst at QinetiQ US, your primary responsibilities will include system administration for the HxGN EAM application, user onboarding, and developing dashboards and analytical models. You'll also be tasked with ensuring data quality, providing technical expertise in data management, and training users on reporting tools. Your key role will involve tracking KPIs to assess program performance and support decision-making processes.

To qualify for the Data Metrics Analyst position at QinetiQ US, you need a BS/BA in a relevant field, with the possibility of substituting additional relevant experience for formal education. A minimum of 5 years’ experience in data analysis, familiarity with enterprise asset management systems, and a Secret Clearance are essential. Strong communication skills and a self-starter mentality will help you excel in this role.

Working as a Data Metrics Analyst at QinetiQ US means being part of a diverse and inclusive team that encourages you to bring your authentic self to work. The environment fosters creativity and collaboration, allowing you to tackle complex challenges with innovative solutions. You'll receive support for your professional development as well as your personal well-being, ensuring a balanced and fulfilling career.

In your role as a Data Metrics Analyst at QinetiQ US, you will primarily work with the HxGN EAM application, managing its administration and user access. You'll also utilize various data sources, databases, and visualization platforms to create dashboards and analytical models. Your technical skills will be vital in data cleansing and mining activities to deliver high-quality insights.

As a Data Metrics Analyst at QinetiQ US, you will have ample opportunities for professional growth. You'll gain exposure to large-scale projects spanning multiple years and locations, expanding your skill set and experience. With a commitment to employee development, QinetiQ US provides training and resources to help you navigate your career path and reach your full potential.

When discussing your experience with data analysis tools, focus on specific software or platforms you have used, such as Excel, Tableau, or specific ERP systems. Highlight how you utilized these tools to derive insights, create visualizations, or support decision-making in previous roles.

In answering this question, mention specific KPIs relevant to your previous positions. Discuss how you tracked them, what insights you gained, and how they influenced management decisions. Use concrete examples to illustrate your points.

Describe the processes and techniques you use to verify data accuracy, such as data cleaning methods, validation techniques, or regular audits. Emphasize your attention to detail and the importance of reliable data in making informed decisions.

Provide a specific scenario where you identified a data issue and implemented a solution. Detail your thought process, the steps you took, and the positive outcome. This showcases your analytical skills and problem-solving abilities.

Discuss your experience creating visual reports and dashboards. Explain the software you've used and how you tailored your visuals to meet the needs of different stakeholders. Emphasize how effective visualization can drive understanding and decision-making.

Share a specific instance where you conducted a training session or created materials for others to learn about data tools. Highlight how you adapted your teaching style to meet the audience's needs and the impact of your training.

Explain your approach to project management, such as using tools or methodologies (like Agile or time blocking). Discuss how you assess project priorities based on deadlines and stakeholder requirements.

Detail the techniques and tools you are familiar with that aid in data mining, such as SQL for querying databases. Be prepared to explain how you've employed these methods to uncover trends or patterns in data.

Share how you keep your skills updated, whether through online courses, reading industry blogs, or participating in professional networks. This shows your commitment to continuous learning in the field of data analysis.

Discuss your familiarity with specific enterprise asset management systems you have worked with, such as HxGN EAM. Highlight your responsibilities, any projects you've been involved in, and how your expertise in these systems can contribute to success at QinetiQ US.