Job Summary
We are seeking a highly analytical Data Analyst to support both IVA and VA initiatives. The ideal candidate will be responsible for collecting, interpreting, and analyzing data to identify trends, uncover insights, and provide actionable recommendations that drive business decisions and operational improvements.
Key Responsibilities
- Gather, clean, validate, and analyze data from multiple sources.
- Develop reports, dashboards, and visualizations to monitor key business metrics.
- Identify trends, patterns, risks, and opportunities through data analysis.
- Partner with IVA and VA stakeholders to understand business requirements and translate them into analytical solutions.
- Generate actionable insights and recommendations to support strategic and operational decision-making.
- Perform ad hoc analysis to address business questions and challenges.
- Present findings and recommendations to business and leadership teams.
- Ensure data accuracy, consistency, and integrity across reporting processes.
- Continuously improve reporting frameworks, metrics, and analytical methodologies.
Skill Requirements
- Bachelor's degree in Data Analytics, Statistics, Mathematics, Computer Science, Business Analytics, or a related field.
- 3+ years of experience in data analysis, business intelligence, or a related role.
- Strong analytical and problem-solving skills.
- Advanced proficiency in SQL for data extraction and analysis.
- Experience with data visualization tools such as Power BI, Tableau, or similar platforms.
- Strong proficiency in Microsoft Excel.
- Experience working with large datasets and complex data structures.
- Excellent communication and presentation skills.
- Ability to translate data findings into clear business recommendations.
Other Requirements
- Experience supporting AI, analytics, automation, IVA, or VA-related programs.
- Knowledge of Python, R, or other analytics/programming languages.
- Experience with cloud-based data platforms such as Azure, AWS, or Google Cloud.
- Familiarity with predictive analytics, statistical modeling, and data mining techniques.