Marketing Data Analyst

MR DIY International; Seri Kembangan; On-site; MYR 60,000 - 100,000; Full time

Job summary

MR DIY International is seeking a data analytics–driven marketing insights professional to lead campaign measurement, loyalty experimentation and regional analytics. You will define KPIs, run A/B tests, and evaluate ROI across festive campaigns and brand initiatives.

You will extract and model sales, customer and marketing data, build dashboards in Power BI or Holistics, and deliver timely insights with clear recommendations to management and cross-functional teams.

Qualifications

• Bachelor's degree in Business Analytics, Statistics, Mathematics, Information Systems, Economics, Marketing or related discipline.
• At least 4 years of relevant experience in data analytics, business intelligence or marketing analytics.
• Strong SQL and Excel skills, with dashboards in Power BI, Holistics or an equivalent platform.
• Practical understanding of experimental design, A/B testing, statistical significance, confidence intervals and bias.
• Demonstrated ability to use AI tools in analytical workflows and improve efficiency.
• Able to communicate complex findings to non-technical stakeholders in business English.

Responsibilities

• Define campaign objectives, KPIs and measurement plans for campaigns, brand initiatives and events.
• Estimate incremental sales, transactions, and ROI using test/control groups and before-and-after comparisons.
• Design and evaluate loyalty tests, customer journeys and metrics such as retention and lifetime value.
• Extract, clean, validate and analyse sales, store, product, marketing and customer data.
• Build and maintain dashboards and KPI trackers in Power BI or Holistics and present findings with clear recommendations.

Skills

Data analytics

BI dashboards

Marketing analytics

A/B testing

SQL

Excel

AI in analytics

Stakeholder mgmt

Business English

Statistical thinking

Education

Bachelor's degree

Tools

Power BI

Holistics

Job description

Job Responsibilities

Marketing impact measurement

• Define campaign objectives, key performance indicators (KPIs) and measurement plans before launch for festive and thematic campaigns, brand initiatives and on-ground events.
• Estimate incremental sales, transactions and contribution profit using appropriate test and control groups, including matched stores where suitable. Use before-and-after comparisons where appropriate, account for seasonality and other promotions, and explain uncertainty and attribution limits.
• Evaluate return on investment (ROI) and the duration of campaign impact, using cost and profit definitions agreed with Finance. Combine sales analysis with brand health and survey findings to recommend improvements to campaign strategy and spending.

Loyalty experimentation and customer analytics

• Design and evaluate A/B tests for loyalty offers, push notifications, rewards and customer journeys. Define hypotheses, eligibility, randomised test and control groups, sample sizes, test duration, success metrics and commercial safeguards before launch.
• Measure incremental conversion, repeat purchase, visit frequency, basket value, retention and reactivation. Assess contribution after reward and campaign costs, and recommend whether to scale, refine or stop a test.
• Analyse customer segments, cohorts and purchase behaviour to identify growth opportunities. Monitor member acquisition, engagement, points and voucher redemption, lapsing and customer lifetime value where the available data supports reliable estimates.

Business intelligence and daily analytics

• Extract, clean, validate and analyse sales, store, product, marketing and customer data. Investigate data quality issues and deliver accurate recurring reports and timely ad hoc analysis for management and business teams.
• Build and maintain dashboards and KPI trackers in Power BI, Holistics or equivalent tools. Apply consistent metric definitions and translate findings into concise presentations with practical recommendations, clear assumptions and analytical limitations.

AI adoption and analytical efficiency

• Use company-approved AI tools to accelerate data queries, exploration, coding, reporting and insight generation. Validate generated queries and results against trusted data and business definitions, and apply sound analytical judgement.
• Automate repeatable reporting and analytical tasks, and document reusable workflows. Follow company requirements for data access, customer privacy and the use of confidential information in AI tools.

Regional performance and business support

• Track regional marketing budgets, expenditure, forecasts and sales-to-expenditure ratios. Explain material budget variances and support planning and spending decisions.
• Conduct market, competitor and brand health analysis, taking account of differences between markets, to support marketing planning and regional business decisions.
• Manage agreed analytical projects and stakeholder requests from scoping to delivery. Work with Marketing, CRM, Finance, IT, data teams and vendors on data requirements, data warehouse integration, CRM enhancements, user acceptance testing and issue resolution. Maintain standard operating procedures (SOPs) and reporting documentation.

Maintain standard operating procedures (SOPs) and reporting documentation.

Job Requirements

Essential

• Bachelor's degree in Business Analytics, Statistics, Mathematics, Information Systems, Economics, Marketing or a related discipline, or equivalent practical experience.
• At least 4 years of relevant experience in data analytics, business intelligence or marketing analytics, with the ability to independently manage analytical projects and stakeholder requests.
• Strong SQL and Excel skills, with hands-on experience building dashboards in Power BI, Holistics or an equivalent platform. Able to work with large transactional datasets and validate data quality.
• Practical understanding of experimental design, A/B testing, statistical significance, confidence intervals and bias. Able to distinguish observed performance differences from incremental campaign impact.
• Demonstrated ability to use AI tools in analytical workflows, explain how outputs were validated, and identify opportunities to improve efficiency.
• Strong commercial thinking, problem-solving skills and attention to detail. Able to explain complex findings clearly to non-technical stakeholders, communicate in business English and manage competing deadlines.

Preferred

• Experience in marketing performance measurement, CRM or loyalty programmes, ideally within retail or another high-volume consumer business.
• Experience with customer segmentation, retention, lifetime value, campaign ROI, brand research or regional marketing budget analysis.
• Python or R for analysis and automation; familiarity with data warehouses, semantic layers, CRM platforms or customer data integration.
• Mandarin language skills would be an advantage.