Data Analyst

Qualifications
• Bachelor or Master’s degree in Computer Science or Engineering Mathematics, Industrial Engineering or Management.
• Minimum of 5 years of experience in the field.
• Experience in data analysis, designing, reports development with 3+ years of experience in Life Insurance, Health Insurance or Banking industry.
• Must be expert in PowerBI reports development.
• Database management system programming (e.g. Oracle, Microsoft SQL Server) ·
• User interface and query software ·
• Agile methodologies·
• Predictive modeling, NLP and text analysis ·
• Data modeling tools (e.g. ERWin, Enterprise Architect and Visio) ·
• Data mining
• ETL tools - UNIX, Linux, Solaris and MS Windows, Hadoop and NoSQL databases
• Data visualization
• Strong interest in the latest relevant tools and technologies
• Strong analytical and problem solving capabilities
• Excellent communication skills
• Knowledge of latest analytics developments/trends.

Job Description
As a Data Analyst, you will be responsible for turning data into information, information into insight, and insight into business decisions. You will conduct full lifecycle analysis to include requirements, activities, and design. Data analysts will develop analysis and reporting capabilities and will also monitor performance and quality control plans to identify improvements.

1. Data Transformation: Convert raw data into meaningful information that can guide business strategies.
2. Lifecycle Analysis: Manage the entire lifecycle of data analysis, from gathering requirements to activity coordination and design implementation.
3. Develop reports and refine analysis and reporting tools to provide clear insights into business performance.
4. Continuously monitor and assess performance metrics to ensure optimal operation and identify areas for improvement.
5. Implement and oversee quality control measures to maintain the integrity and accuracy of data analysis.
6. Synthesize complex data sets to extract key trends and insights that drive decision-making processes
7. Work closely with cross-functional teams to prioritize data and analytics needs and support data-driven decisions.
8. Proactively seek out and recommend process enhancements to streamline data collection and analysis procedures.
9. Constantly monitor, refine and report on the performance of data management systems.
10. Maintain a corporate repository of all data analysis artifacts and procedures.
11. Compliance
12. Perform other functions as may be assigned.