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Company Overview: This telecommunications conglomerate is a major player in the Singaporean market, offering a comprehensive suite of services including mobile phone services within Singapore and through subsidiaries in other countries, fixed-line telephony services, internet access and pay television services, data center and cloud computing services, cybersecurity solutions, and digital services like mobile advertising and digital media.
Data & Analytics Consultant (Nucleus Graduate Programme)
What will you do?
Translate customer pain-points into problem statements, develop analytics solutions, and engagingly present results and learnings to both technical and non-technical audiences.
Contribute to the building and maintaining of end-to-end data pipelines to bring information from source systems, harmonize and cleanse data to support analytics solutions.
Contribute to scoping of data inputs, data cleaning and pre-processing, feature engineering, building analytics solution, deploying to production, conducting testing, and improving analytics solution by iterations.
Participate in technical design sessions with cross-functional teams to define data process flow, data definition, data & analytics solution requirements and specifications.
Work closely with project managers and technical leads to provide regular status reporting and support them to refine issues/problem statements and propose/evaluate relevant analytics solutions.
Work in interdisciplinary teams that combine technical, business and analytics competencies that deliver work in waterfall or agile software development lifecycle methodologies.
The ideal candidate should possess:
Basic competency in two or more of the following areas preferred:
Data visualization tool (e.g., Tableau, Qlik, PowerBI)
SQL knowledge
Programming or scripting language (e.g., Python, R, Java)
Analytical software (e.g., SAS)
Distributed architectures (e.g., HDFS, Hive)
Ability to analyze and break down complex concepts and technical findings into clear and simple language for communication to team members and clients.
Ability to link industry-specific business requirements to BI, Analytics, and Big Data solutions.
Degree in Computer Science, Computer Engineering, Engineering, Information Systems, Business Analytics, Mathematics, Statistics, Economics, Physics, or other related disciplines that possess an analytical and quantitative component from a reputable institution.
Fresh graduate or less than 2 years of relevant working experience.
Additional experience good to have:
Proficiency in AWS, Azure, Cloudera (or other cloud services), data pipeline and database development.
Knowledge of statistical modeling, predictive analytics, or machine learning.
Hands-on experience in setting up and using toolkits such as Docker, VMs, Git, SSH, REST APIs.
Certification in leading data analytics platforms such as Tableau, Qlik, Informatica, Talend, Microsoft, SAS, IBM.
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