Manager, Data Analytics

Hong Leong Assurance Berhad; Selangor; On-site; MYR 90,000 - 120,000; Full time

Job summary

A leading company in the financial services sector is seeking a Manager of Data Analytics to enhance data-driven decision-making. This full-time role involves strategic alignment, stakeholder management, and leading a team of analysts to drive insights and innovation in data analytics. The ideal candidate will have extensive experience in data analysis, a strong background in leadership, and proficiency in advanced analytical techniques.

Qualifications

• 5+ years in business intelligence or data analysis with leadership experience.
• Experience in the Insurance or Financial Services industry preferred.

Responsibilities

• Drive data analytics initiatives aligned with business strategy.
• Lead and develop the data analytics team, managing performance and budget.
• Oversee data analytics projects ensuring timely delivery.

Skills

Data Analysis

Stakeholder Management

Problem-solving

Communication

Education

Bachelor's Degree

Tools

SQL

Python

Power BI

Tableau

Job description

About the role

As the Manager, Data Analytics at Hong Leong Assurance Berhad, you will play a crucial role in driving the company's data-driven decision making. This full-time position is based in Petaling Jaya, Selangor, and offers exciting opportunities to leverage your expertise in analysis and reporting to support the banking and financial services operations.

Key Responsibilities:

• Strategic Alignment: Drive and execute the overall business strategy and translate it into data analytics initiatives that support key objectives and business value.
• Data Strategy and Governance: Lead the development and implementation of the data analytics strategy, ensuring data quality, integrity, and compliance with governance policies.
• Stakeholder Management: Build and maintain strong relationships with key stakeholders across different business units to understand their needs, define project scope, and communicate analytical findings effectively.
• Project Management: Oversee and manage data analytics projects from initiation to completion, ensuring they are delivered on time, within budget, and meet business requirements.
• Advanced Analytics and Innovation: Drive the adoption of advanced analytical techniques (e.g., machine learning, statistical modeling) and explore new data sources and technologies to enhance analytical capabilities.
• Data Visualization and Reporting Strategy: Define standards and best practices for data visualization and reporting to ensure clarity, consistency, and actionable insights across the organization.
• Business Insight and Recommendations: Lead the analysis of complex data sets to identify critical trends, patterns, and opportunities, and translate these findings into strategic recommendations for business improvement and growth.
• Campaign Analytics Leadership: Lead the analysis of marketing campaigns, including customer targeting, post-implementation reviews, and the development of strategies for continuous improvement.
• Performance Monitoring and Metrics: Define and monitor key metrics to track the performance of business initiatives and identify areas for data-driven optimization.
• Collaboration and Communication: Foster strong collaboration with IT and other departments to ensure seamless data access and the effective implementation of analytical solutions.
• Risk Management: Identify potential risks and challenges related to data analytics projects and team operations, and develop mitigation strategies.

Managerial Responsibilities:

• Lead and Develop the Data Analytics Team: Manage, mentor, and coach a team of data analysts (including Assistant Managers) to enhance their skills and productivity. Foster a collaborative and high-performing team environment.
• Budget Management: Manage the budget allocated to the data analytics team and ensure resources are utilized effectively.
• Performance Management: Set clear performance expectations for team members, provide regular feedback, conduct performance reviews, and identify opportunities for individual growth and development.

Education and Experience:

• At least 5 years of progressive experience in business intelligence, data analysis, reporting, or a related field. This experience should demonstrate increasing responsibility and complexity in analytical projects.
• Experience (ideally 3+ years within the 5+) in a leadership or supervisory role within a data analytics team, showcasing the ability to mentor, guide, and manage analysts.
• Experience working within the Insurance or Financial Services industry is highly preferred

Technical Proficiency:

• Expertise in Data Manipulation and Analysis: Proven mastery of SQL and at least one programming language commonly used for data analysis (e.g., Python, R).
• Advanced Data Visualization Skills: Deep proficiency in creating interactive dashboards and insightful reports using tools like Power BI and Tableau.
• Experience with Data Warehousing and ETL Processes: Familiarity with data warehousing concepts and ETL (Extract, Transform, Load) processes is beneficial.
• Exposure to Advanced Analytics (Preferred): Experience with statistical modeling, machine learning techniques, and big data technologies would be a strong advantage.

Soft Skills:

• Ability to translate complex data into meaningful, actionable insights for business stakeholders.
• Problem-solving and critical thinking skills with a strong business acumen.
• Communication and presentation skills, with the ability to effectively convey technical information to both technical and non-technical audiences.
• Stakeholder management skills, including the ability to build relationships, influence, and manage expectations across different business units.
• Strong leadership and team management skills, with experience in mentoring and developing team members.