Manager, Data Analytics

MOL AccessPortal; Kuala Lumpur; On-site; MYR 120,000 - 160,000; Full time

Job summary

A leading data analytics firm in Kuala Lumpur seeks a Manager, Data Analytics to lead the analytics team. This role includes developing strategies that drive business insights, managing advanced analytics tools, and delivering key reports. Ideal candidates should possess strong data analysis skills, experience with SQL, Python, R, and data visualization tools like Tableau and Power BI. The position emphasizes collaboration with various business units to ensure the effective use of data across the organization.

Qualifications

• Proven experience in data analysis and team leadership.
• Strong skills in SQL, Python, and R for data analytics.
• Experience with data visualization tools like Tableau and Power BI.

Responsibilities

• Develop and execute data analytics strategy aligned with business goals.
• Lead a team of analysts and scientists to enhance analytical skills.
• Oversee the implementation of advanced analytics tools and platforms.
• Develop dashboards and reports to communicate business insights.
• Partner with cross-functional teams for aligned analytics initiatives.

Skills

Data analysis

Team leadership

SQL

Python

R

Tableau

Power BI

Machine learning

Predictive modeling

Data governance

Job description

The Manager, Data Analytics will oversee the data analytics team, leading efforts to provide actionable insights that drive strategic decision-making across the organization. This role involves managing the development of analytics solutions, ensuring data quality, and aligning analytics initiatives with business goals. You will work closely with key stakeholders to translate business needs into data-driven strategies and support the company’s overall performance through advanced analytics and reporting.

Key Responsibilities:

Develop and execute a comprehensive data analytics strategy to support the company’s business goals.

Lead the creation of analytics frameworks and processes to generate insights that inform product development, marketing, and operational efficiency.

Ensure that data-driven insights are used to optimize business performance and enhance customer experiences.

Manage, mentor, and develop a team of data analysts and data scientists, ensuring continuous improvement in analytical skills and output.

Foster a collaborative, data-driven culture within the team and across the organization.

Set clear goals and KPIs for the team, providing regular feedback and performance evaluations.

Data Tools & Infrastructure:

Oversee the implementation and use of advanced analytics tools (e.g., SQL, Python, R) and data visualization platforms (e.g., Tableau, Power BI).

Collaborate with engineering and IT teams to ensure the data infrastructure supports the organization’s analytics needs, including data collection, integration, and reporting systems.

Continuously assess and implement new tools and technologies that enhance data analytics capabilities.

Data-Driven Insights & Reporting:

Develop and maintain reports, dashboards, and visualizations that communicate key business insights to stakeholders at all levels of the organization.

Identify trends, patterns, and opportunities from large datasets, and provide actionable recommendations to optimize business operations.

Collaborate with business units to define key metrics and ensure that performance is tracked against goals.

Collaboration & Stakeholder Management:

Partner with cross-functional teams including marketing, finance, product, and operations to ensure alignment of analytics initiatives with business objectives.

Act as the key point of contact for analytics across the organization, ensuring stakeholders have access to accurate and timely data.

Communicate complex data insights in a clear and actionable way to both technical and non-technical stakeholders.

Advanced Analytics & Predictive Modeling:

Lead initiatives that leverage advanced analytics techniques, such as machine learning and predictive modeling, to solve business challenges.

Develop models to forecast customer behavior, optimize marketing strategies, and enhance product performance.

Ensure continuous improvement in analytics processes and methods to stay ahead of industry trends and best practices.

Data Governance & Quality:

Ensure data accuracy, integrity, and consistency across all analytics platforms and tools.

Establish data governance processes to maintain high standards in data quality and ensure compliance with relevant regulations.

Work with the data engineering team to enhance data collection and warehousing for more accurate and reliable analytics.