About the Role
Turn statistical thinking into measurable business insight. As a Senior Data Scientist, you will develop predictive models, test hypotheses and assess how retail campaigns influence customer behaviour and performance.
The role combines hands-on modelling with clear communication to technical and business stakeholders. You will work across the model lifecycle—from development and validation to deployment and monitoring—while collaborating with data science, commercial and marketing teams. The main focus is practical statistics, machine learning and experimentation, with AI-related work forming part of the remit.
Requirements
Must Have
Bachelor's or Master's degree in Data Science, Computer Science, Statistics or a related field.
Relevant hands-on data science experience and the ability to contribute at senior level; approximately 3–4 years of relevant experience is considered suitable.
Strong programming skills in Python or a similar language.
Practical knowledge of statistics, predictive modelling and machine-learning techniques.
Strong analytical thinking, problem-solving and stakeholder communication skills.
Basic experience with data visualisation tools such as Power BI, Tableau or Qlik; no single platform is specified as mandatory.
Relevant Technical Focus
Hypothesis formulation and A/B testing.
Predictive methods such as gradient boosting, random forests and decision trees.
Ability to connect analytical findings with business outcomes.
Responsibilities
Modelling & Experimentation
• Develop, validate and deploy predictive models using statistical and machine-learning methods.
• Formulate hypotheses and apply A/B testing to evaluate promotion effectiveness.
• Compare campaign and control-store performance and analyse shopper behaviour.
• Monitor deployed models and optimise performance.
Business Insight & Delivery
• Identify data-driven opportunities with data science, commercial and marketing teams.
• Extract actionable insights from large, complex datasets.
• Present findings and recommendations clearly to technical and non-technical stakeholders.
• Integrate analytical solutions into existing systems and business processes.
• Keep current with relevant developments in data science.
Salary and Benefits
• Discussed monthly salary ceiling: approximately MR 10,000. Base salary versus total-package treatment is to be confirmed.
• Permanent employment directly with this company.
• Hybrid arrangement: two office days and three work-from-home days per week.
• Bonus, insurance, leave, allowances and other benefit details are to be confirmed.
About the Company
This company provides digital solutions and analytics services that help businesses understand customers and make better decisions. Its work spans retail analytics, personalised experiences, AI and machine learning, and data visualisation.
By combining analytical expertise with commercial and marketing collaboration, this company turns complex datasets into practical insights and business applications. This role focuses on the impact of promotions, shopper behaviour and business growth in Malaysia.