SA, Data Scientist

WHY JOIN US?

• We practice a vibrant & energetic office culture.
• We provide opportunities for career advancement within the company.
• Good performance is always rewarded accordingly.

“ It's our people that make Astro Malaysia’s leading entertainment company. We are an inclusive employer, to enable everyone at Astro to be their best. We embrace differences – we celebrate it, we support it, and we thrive on it for the benefit of our employees, our products/services and our community. We also understand and appreciate that diversity is a driver of creativity and innovation, which will make our business more competitive, compelling and profitable. ”

Job Responsibilities Audience Segmentation & Customer Analytics

• Develop and maintain PayTV and Digital audience segments using behavioral, demographic, transactional, and engagement data.
• Build customer profiles and audience taxonomies to support personalization, targeting, and campaign optimization.
• Perform audience sizing, profiling, and overlap analysis across multiple platforms and products.
• Support the development of a unified audience view by integrating customer, viewing, digital, and third-party data sources.

Data Science & Modeling

• Apply statistical and machine learning techniques to identify audience clusters, customer affinities, and engagement drivers.
• Develop propensity, churn, content affinity, and customer value models to support business use cases.
• Conduct exploratory data analysis to uncover trends, patterns, and growth opportunities.
• Evaluate model performance and continuously improve segmentation methodologies.

Business Insights & Stakeholder Support

• Translate complex analytical findings into actionable business recommendations.
• Collaborate closely with Marketing, Product, Media Sales, and Content teams to address audience-related business challenges.
• Support campaign measurement, audience effectiveness analysis, and customer engagement initiatives.
• Prepare executive-ready reports, and presentations that communicate key insights and opportunities.

Requirements Technical Skills

• Degree in Data Science, Statistics, Mathematics, Computer Science, Economics, Engineering, or a related quantitative field.
• 2-5 years of experience in data analytics, customer analytics, data science, or audience measurement.
• Proficiency in Python and SQL for data extraction, processing, and analysis.
• Experience working with large-scale datasets in cloud-based data environments (AWS, Databricks, Azure, Snowflake, Redshift, Spark, etc.).
• Familiarity with machine learning and statistical techniques such as:
• Clustering and Segmentation
• Regression Models
• Decision Trees and Random Forests
• Gradient Boosting Models
• Customer Propensity Modeling
• Time Series Analysis
• Recommendation Systems

Audience & Business Analytics

• Experience in customer segmentation, audience measurement, customer insights, CRM analytics, or digital analytics.
• Understanding of customer lifecycle management, audience activation, personalization, and campaign analytics.
• Experience working with digital, streaming, media, content, telecommunications, or subscription-based businesses is an advantage.
• Familiarity with audience measurement tools, web analytics, or CDP/DMP platforms is preferred.

Visualization & Communication

• Experience using BI and visualization tools such as Power BI, Tableau, QuickSight, or similar platforms.
• Strong storytelling skills with the ability to communicate analytical insights to both technical and non-technical stakeholders.
• Excellent presentation, written, and verbal communication skills.

Core Competencies

• Strong analytical and problem-solving mindset.
• Ability to translate business requirements into data-driven solutions.
• Self-motivated, curious, and eager to learn new technologies and analytical approaches.
• Ability to manage multiple priorities in a fast-paced, cross-functional environment.
• Strong stakeholder management and collaboration skills.rial engineering)
• 2 years of relevant work experience in data analysis or related field. (e.g., as a statistician / data scientist / computational biologist / bioinformatician).
• Strong Machine Learning and Data Mining background. Including ability to build and interpret machine learning models of complex, high-dimensional systems.
• Experience processing large-scale data prototyping, then production-level algorithms.
• Ability to work with incomplete or imperfect data to extract usable information.
• Attention to detail, data accuracy and quality of output.
• Experience with large scale distributed data processing frameworks like Hadoop and Spark
• Experience of high-level programming language for analysis (e.g. Spark, Scala, Python, R, Java) a plus
• Highly self-motivated, results driven and data driven. Ability to work in a fast-paced dynamic environment.
• Experience in audience and payment sciences is a plus.
• Traits
• Be positive, passionate, collaborative, self-motivated, responsible, dependable and enthusiastic team player.
• Experience articulating business questions and using mathematical techniques to arrive at an answer using available data. Experience translating analysis results into business recommendations.
• Demonstrated skills in selecting the right statistical tools given a data analysis problem. Demonstrated effective written and verbal communication skills.
• Demonstrated leadership and self-direction. Demonstrated willingness to both teach others and learn new techniques.