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Decisioning Analytics Specialist

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Onsite

Decisioning Analytics Specialist

CelcomDigi

Decisioning Analytics Specialist

Skills

SQL QueriesBig DataPythonData ScienceRData AnalysisMachine LearningSAP SuccessFactors

1 month ago

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Important information


Location:

Petaling Jaya, Selangor, Malaysia

Work mode:

Onsite

Published on:

11 September 2026

What they need


As a Data Scientist, you will play a key role in delivering high-impact analytics and machine learning solutions at scale for a leading telecom operator. You’ll work on complex, real-world problems, influence business decisions, and help shape how advanced analytics is embedded across the organisation. This role offers hands-on ownership, exposure to senior stakeholders, and the opportunity to grow into broader technical or leadership responsibilities.

Responsibilities

  • Lead the development and delivery of advanced analytics and machine learning models to address key business opportunities and gaps.
  • Partner with business stakeholders with minimal supervision, clearly communicating insights, assumptions, and model outcomes.
  • Collaborate with peers across data science, engineering, and analytics teams on cross-functional problem solving.
  • Continuously enhance models through feature engineering, new data sources, and experimentation to improve business performance.
  • Contribute to setting best practices, standards, and re-usable assets across the data science team.
  • Translate ambiguous business problems into well-structured analytical approaches and recommend appropriate modelling techniques.

Requirements

  • Bachelor’s degree in Data Science, Actuarial Science, Mathematics, Statistics, Computer Science, or related fields.
  • Strong, demonstrable experience delivering analytics and machine learning projects end-to-end.
  • Experience in the telecommunications industry is an advantage but not mandatory.
  • Hands-on experience with Python, SQL, R (or equivalent) and big data / distributed processing tools (e.g. Spark).
  • Working knowledge of machine learning algorithms and classifiers.
  • Strong communication, presentation, and analytical skills, with the ability to influence non-technical stakeholders.

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