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Date: 26-May-2022

Location: Petaling Jaya, MY

Company: Celcom Axiata Berhad

Job Description


Requirement gathering, analyze, plan and design methodology to solving business problems by using advance analytics, building and delivering statistical models. 



  1. Build and deliver complex models by using deep learning and advance machine learning techniques to cater for the business gap identified
  2. Assess the problem statement and make decision on the best approach to solve business problems.
  3. Prepare slides and delivers presentations to articulate findings of advance analysis and models to management and necessary stakeholders
  4. Propose new revenue generation by analyzing business gaps for higher incremental revenue
  5. Ability to answer customers' questions independently and share modelling output effectively
  6. Collaborate and establish a close working relationship with stakeholders to ensure business requirement is met and delivered in timely manner
  7. Collaborating with peers for cross-functional problem solving
  8. Proactively share code and guide others in sharing in internal repo.
  9. Continuously seek for new innovative ways or new data sources to improve the models/increase business performance.
  10. Analyze system gaps required to provide business solution and drive the implementation to fix the gaps


•    Bachelor’s Degree in Finance / Actuarial Science / Mathematics / Statistics / Computer Sciences 
•    Master’s Degree and/or Professional Qualifications will be an added advantage.
•    Minimum 10 or more years of work experience of relevant quantitative and qualitative research and analytics and machine learning 
•    Experience in telecommunications industry will be an added advantage.


•    Knowledge of telecommunication industry with knowledge of business/functional areas is preferred 
•    Advance knowledge SQL, Python, R, Spark R or equivalent 
•    Advanced knowledge of Big Data analysis and management with Apache tools such as Cloudera, Zookeeper, Pig, Hive, HBase etc 
•    Strong experience with machine learning algorithms and classifiers such as k-NN, Naive Bayes, SVM, Random Forest, Linear Regression, ARIMA, Neural Nets, Deep learning, etc. 
•    Advanced knowledge of technical work-flow tracking through tools such as Linus, Apache Sqoop and Apache Oozie 
•    Good communication, presentation, and analytical skills 

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