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:

o   Clustering and Segmentation

o   Regression Models

o   Decision Trees and Random Forests

o   Gradient Boosting Models

o   Customer Propensity Modeling

o   Time Series Analysis

o   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.