Senior Data and Reporting Analyst

at  MetLife

Location(s)

• Posting Location: Melbourne, Victoria
• Posting Location: Sydney, New South Wales

Country
Australia
Working Schedule
Full-Time
Work Arrangement
Hybrid
Relocation Assistance Available
No
Posted Date
17-Jun-2024
Job ID
2707

KNOWLEDGE/SKILLS/COMPETENCIES REQUIRED:

• Data Analysis: Expertise in analyzing large datasets and identifying trends, patterns, and opportunities for optimization.

• Predictive Modeling: Proficiency in building and maintaining predictive models and other analytical tools.

• Reporting and Visualization: Strong skills in designing and developing reports and dashboards using tools like Power BI, Tableau, or similar.
• Analytical Skills: Excellent problem-solving and analytical skills to translate complex data into actionable insights.
• Communication: Exceptional communication skills to effectively convey data findings to non-technical stakeholders.
• Technical Proficiency: Proficiency in data analysis software and programming languages such as SQL, Python, or R.
• Collaboration: Ability to work collaboratively with cross-functional teams to achieve business objectives.
• Data Governance: Knowledge of data governance principles and practices to ensure data integrity and quality.
• Attention to Detail: High attention to detail to ensure accuracy and reliability in data analysis and reporting.
• Strategic Thinking: Ability to leverage data to provide strategic insights and support decision-making processes.

QUALIFICATIONS REQUIRED:

Essential

• Certifications in data analysis or related fields

Desirable

• Bachelor’s Degree in Data Science, Statistics, Computer Science, or a related field.
• Minimum 5 years of experience in data analysis, reporting, and predictive modeling.
• Experience in the insurance or financial services industry..
• ..

SUMMARY OF RESPONSIBILITIES:

This role is essential for ensuring that the HSECi team utilizes data effectively to drive strategic decision-making, optimize operations, and enhance the overall member experience.
The Senior Data and Reporting Analyst is responsible for leveraging data to provide strategic insights and support decision-making processes across the HSECi team. This role involves analyzing large datasets, translating complex data into actionable insights, and developing predictive models and analytical tools to optimize operations and forecast customer behavior.

PRINCIPAL RESPONSIBILITIES:

Data Analysis and Insights:

• Analyze large datasets containing customer information, operational metrics, and other relevant data to identify trends, patterns, and opportunities for optimization.
• Leverage data to provide strategic insights and support decision-making processes across HSECi.
• Translate complex data into clear and concise insights and actionable recommendations.
• Identify trends and patterns in insurance policyholder data and operational transaction data, providing actionable insights to support strategic decision-making and business planning.
• Monitor the performance of insurance policies and operational processes against established targets and benchmarks, identifying areas for improvement and optimisation.

Reporting and Dashboards:

• Design and develop comprehensive reports and interactive dashboards to visualize data and track key performance indicators (KPIs).
• Ensure reports and dashboards are accurate, timely, and tailored to meet the needs of various stakeholders.

Predictive Modeling and Analytics:

• Build and maintain predictive models, segmentation models, and other analytical tools to forecast customer behavior and inform strategic initiatives.
• Continuously improve and refine models to enhance their accuracy and effectiveness.
• Develop and maintain complex financial models built from primary and secondary data sources.

Collaboration and Communication:

• Collaborate with cross-functional teams , including actuarial, underwriting, product, claims and marketing, to understand data requirements and deliver insights that drive business outcomes.
• Communicate complex data findings and insights effectively to non-technical stakeholders.

Data Governance and Quality Management:

• Define and enforce data standards and governance to ensure data integrity, quality, and security.
• Implement quality management frameworks to maintain high standards in data analysis and reporting.

Continuous Improvement:

• Stay updated with the latest data analytics tools, techniques, and industry trends to ensure best practices are applied.
• Identify and implement process improvements to enhance data analysis and reporting capabilities.