data analyst for data-driven decision-making

Intetics is an American technology company specializing in custom software application development, distributed professional teams, software product quality assessment, and digital solutions.

• Analyze large and complex datasets using statistical and quantitative methods;
• Apply regression analysis, hypothesis testing, probability analysis, simulations, and time-series analysis to identify patterns and explain trends;
• Validate analytical outputs, identify anomalies and outliers, and distinguish meaningful issues from normal variability;
• Translate analytical findings into practical recommendations for customers and internal stakeholders;
• Support business decisions with clear, evidence-based insights;
• Design and develop dashboards, reports, and visualizations;
• Adapt reporting formats and detail levels for different audiences;
• Monitor dashboards and reports to ensure accuracy as data sources, business rules, and system configurations change;
• Present analytical findings to technical and non-technical stakeholders;
• Research relevant datasets, industry benchmarks, and external context;
• Assess data quality and investigate inconsistencies or unexpected results;
• Use AI tools to accelerate research, summarize findings, prepare documentation, and support analytical and quality-assurance workflows;
• Stay informed about relevant analytical tools, data sources, methodologies, and industry best practices.

• Bachelor's degree in Statistics, Mathematics, Economics, Computer Science, or another quantitative field;
• At least 3 years of professional experience in data analysis, business intelligence, or a related role;
• Strong knowledge of statistics and quantitative analysis;
• Advanced SQL skills and experience working with large datasets;
• Strong proficiency with at least one data visualization platform, such as Power BI or Tableau;
• Proficiency in Python, R, or another statistical programming language;
• Experience creating dashboards, reports, and analytical presentations for different stakeholder groups;
• Excellent written and verbal communication skills, with the ability to explain complex findings in clear, practical language;
• Nice to have: Master's degree in a quantitative field, experience with cloud data platforms such as AWS, Microsoft Azure, or Google Cloud Platform, understanding of machine learning concepts and practical applications, experience with A/B testing and experimental design, familiarity with data governance and data quality practices, experience using AI tools to improve research, analysis, documentation, or quality-assurance workflows.

• Long-term position with an immediate start.