Data Scientist

PT. Indosat Tbk; Jakarta Utara; On-site; IDR 300.000.000 - 400.000.000; Full time

Job summary

A telecommunications company based in Jakarta Utara is seeking a Data Science professional to create data mining architectures and apply machine learning techniques. The ideal candidate will engage in statistical reporting and data analysis across various business areas, including Market Economics and Supply Chain. Responsibilities include collaborating with stakeholders, planning projects, and ensuring quality outcomes. This role requires knowledge of emerging data science principles to drive impactful business decisions.

Responsibilities

• Collaborating with team members to achieve goals.
• Focusing on continuous improvement in processes.
• Planning and organizing projects effectively.
• Analyzing data to inform business decisions.
• Ensuring quality orientation in all activities.
• Building customer loyalty through service excellence.

Job description

Job Summary

Data Science work includes: Creating data mining architectures/models/protocols, statistical reporting, and data analysis methodologies to identify trends in large data sets. Analysis may be applied to various areas of the business (e.g., Market Economics, Supply Chain, Marketing/Advertising, Scientific Research, etc.). Researching and applying knowledge of existing and emerging data science principles, theories, and techniques to inform business decisions. Applying and/or implementing Machine Learning (ML) or other Artificial Intelligence (AI) techniques to solve business problems and/or derive actionable business insights. At higher career levels, may conduct scientific research projects with the goal of breaking new ground in data analytics.

Job Responsibilities

Leadership Competencies:

• Collaborating
• Continuous Improvement
• Business Awareness
• Planning and Organizing
• Quality Orientation
• Analysis
• Applied Learning
• Building Customer Loyalty

Technical Competencies

• Business Analysis and Decision Support
• Consulting, Transformation and Enablement
• Database Administration and Performance
• Machine Learning Engineering and MLOps
• Cloud Platforms and Infrastructure-as-Code
• Business Intelligence and Data Products
• Performance Monitoring and Site Reliability
• Data Governance, Quality and Stewardship
• Advanced Analytics and Data Science
• Research, Innovation and Emerging Tech
• Testing, QA and Data Validation
• Security, Privacy and Compliance (Data)
• Data Engineering and Integration Pipelines

Behavioral Expectations

Personality Traits, Internal Stakeholders, External Stakeholders