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.