Officer-Data Scientist

Indosat; Tangerang; Hybrid; IDR 180,000,000 - 300,000,000; Full time

Job summary

Indosat is seeking a Data Scientist to develop and operationalize AI and ML solutions across consumer, enterprise, and corporate domains. You will translate business questions into analytical use cases, design models, and ensure measurable outcomes such as churn reduction, ARPU growth, and cost optimization.

The role leads the full AI lifecycle from data exploration and feature engineering to model deployment and performance tracking, deploying with Vertex AI pipelines and maintaining

Qualifications

• Bachelor’s or Master’s in Data Science, Statistics, Computer Science, or Applied Mathematics.
• 3–6 years of experience in machine learning model development and experimentation, ideally in telecom, fintech, or technology sectors.
• Strong proficiency in Python, SQL, and ML frameworks (TensorFlow, PyTorch, Scikit-learn).
• Experience working with cloud ML platforms (Vertex AI, AWS SageMaker, or Azure ML) and pipeline orchestration.

Responsibilities

• Translate business needs into technical requirements and define model objectives, input data, and success metrics.
• Conduct exploratory data analysis (EDA), cleansing, transformation, and feature selection.
• Build, train, and test machine learning models aligned to business use cases and Responsible AI standards.Engineer new features to improve model performance and capture new business signals.
• Build, test, and maintain Vertex AI pipelines from UDP (Unified Data Platform) to ACE (AI CoE Environment).
• Maintain up-to-date model documentation including data lineage, assumptions, KPIs, and Responsible AI checks.

Skills

Python

SQL

ML frameworks

Responsible AI

Communication

Education

Bachelor’s or Master’s degree in Data Science/Statistics/CS/Applied Math

Tools

TensorFlow

PyTorch

Scikit-learn

Vertex AI

AWS SageMaker

Azure ML

Job description

The Data Scientist plays a pivotal role in developing and operationalizing AI and machine learning solutions that address key business challenges across consumer, enterprise, and corporate domains. This role transforms complex business questions into analytical use cases, designs and trains predictive and prescriptive models, and ensures each model delivers measurable business outcomes such as churn reduction, ARPU growth, cost optimization, and customer satisfaction improvement. Beyond model creation, the Data Scientist leads the full AI lifecycle — from data exploration, feature engineering, and model development to testing, pipeline deployment, and continuous performance tracking. Each model is documented through Model Cards and deployed using Vertex AI pipelines (UDP to ACE) to ensure scalability, transparency, and compliance.By combining deep analytical expertise with Responsible AI practices, the Data Scientist ensures that every solution contributes to embedding AI as a strategic, value-generating capability across the organization.

Responsibilities

• Translate business needs into technical requirements and define model objectives, input data, and success metrics.
• Conduct exploratory data analysis (EDA), cleansing, transformation, and feature selection.
• Build, train, and test machine learning models aligned to business use cases and Responsible AI standards.Engineer new features to improve model performance and capture new business signals.
• Build, test, and maintain Vertex AI pipelines from UDP (Unified Data Platform) to ACE (AI CoE Environment).
• Maintain up-to-date model documentation including data lineage, assumptions, KPIs, and Responsible AI checks.

Qualifications

• Bachelor’s or Master’s degree in Data Science, Statistics, Computer Science, or Applied Mathematics.
• 3–6 years of experience in machine learning model development and experimentation, ideally in telecom, fintech, or technology sectors.
• Strong proficiency in Python, SQL, and ML frameworks (TensorFlow, PyTorch, Scikit-learn).
• Experience working with cloud ML platforms (Vertex AI, AWS SageMaker, or Azure ML) and pipeline orchestration.
• Understanding of Responsible AI, bias testing, and model explainability principles.
• Strong communication and documentation skills for ARS and Model Card preparation.