Data Analyst

ReqID: 2433704 Analytical Skills Strong analytical and critical thinking abilities Ability to identify trends, patterns, and actionable insights from complex datasets Experience performing data mining, root cause analysis, and hypothesis testing Ability to translate business problems into analytical solutions Strong attention to detail with a focus on data accuracy and quality Soft Skills Excellent written and verbal communication skills Strong presentation and storytelling with data capabilities Effective stakeholder management and collaboration Customer-focused mindset with strong business acumen High level of ownership and accountability Ability to prioritize multiple assignments and meet deadlines Adaptability and willingness to learn new tools and technologies Strong teamwork and cross-functional collaboration skills Preferred Skills Exposure to Python for analytics or automation Experience with Microsoft Azure Machine Learning, Microsoft Fabric, or Databricks Knowledge of advanced analytics and automation platforms Microsoft Power BI Data Analyst (PL-300) certification or equivalent is preferred Experience 0–3 years of experience in Business Intelligence, Reporting, Data Analytics, or a related analytical field. Experience analyzing business data and developing clear, accurate, and actionable insights is required. Experience supporting customer-focused organizations or business functions is preferred. Experience developing dashboards, recurring reports, and business performance metrics is desirable. Experience working with cross-functional stakeholders and presenting analytical findings to business audiences is preferred. Qualifications Education Bachelor's degree in Data Science, Computer Science, Statistics, Economics, Mathematics, Information Systems, Engineering, or another quantitative discipline is required. An equivalent combination of education and relevant experience will also be considered. This position may require licensing for compliance with export controls or sanctions regulations. 100% On-Site No