Data Scientist - Decision Intelligence & Agentic Solutions

PT. Indosat Tbk; Jakarta Pusat; On-site; IDR 350,000,000 - 650,000,000; Full time

Job summary

PT. Indosat Tbk is seeking a senior data science professional to turn predictive models into decision-intelligent workflows and agentic solutions.

You will define where models, rules, LLMs, and human approvals apply, and build scalable interfaces for multiple business domains. The role emphasizes practical GenAI capabilities, robust experimentation, and governance over production workflows to deliver measurable business impact in a telecommunications context.

Qualifications

• Minimum bachelor’s degree in STEM, Statistics, Mathematics, Computer Science, Engineering, Economics or another quantitatively rigorous discipline.
• 4–8 years across Data Science, applied ML, decision intelligence or AI product development with evidence of translating analytics into operational actions.
• Hands-on GenAI / agentic experience is highly desirable.

Responsibilities

• Translate priority business workflows into decision-intelligence and agentic use cases with clear value hypotheses.
• Identify where deterministic rules, predictive models, LLMs, agents or human approval should be used.
• Define reusable decision patterns and analytical interfaces that scale across domains.
• Build analytical components for prediction, prioritization, treatment selection and optimization and expose them as inputs.
• Prototype agentic workflows using retrieval, tools, APIs, structured outputs and function calling.
• Design guardrails, confidence thresholds, escalation paths, auditability and monitoring for production workflows.

Skills

Python

SQL

Machine learning

Statistics

Feature engineering

Experimentation

GenAI / agentic capabilities

Decision intelligence

API / tool interfaces

Communication across stakeholders

Education

Bachelor’s degree in STEM, Statistics, Mathematics, Computer Science, Engineering, or Economics

Job description

• Turn analytical intelligence into decisions, interventions and agentic workflows by combining strong Data Science foundations with decision design, workflow reasoning and practical GenAI / agentic capabilities.
• Apply Data Science methods to prediction, prioritization, segmentation, experimentation and optimization, then translate the outputs into decision logic that business workflows can realistically use.
• Define what downstream agents or applications need beyond a model score: context, explanations, constraints, eligibility, confidence, action options and escalation rules.
• Determine where decisions should be deterministic, model-driven, LLM-assisted or human-approved; design safe autonomy boundaries and guardrails.
• Prototype and evaluate agentic workflows using tools, APIs, retrieval, structured outputs and function calling where they add genuine value.
• Measure workflow / agent performance alongside model performance and create feedback loops linking interventions to customer and business outcomes.

Job Description

Strategic Planning

• Translate priority business workflows into decision-intelligence and agentic use cases with clear value hypotheses.
• Identify where deterministic rules, predictive models, LLMs, agents or human approval should be used - and where they should not.
• Define reusable decision patterns and analytical interfaces that can scale across multiple business domains.

Operational

• Build analytical components for prediction, prioritization, treatment selection and optimization, then expose them as usable decision inputs.
• Prototype agentic workflows using retrieval, tools, APIs, structured outputs and function calling where appropriate.
• Design guardrails, confidence thresholds, escalation paths, auditability, evaluation and monitoring for production workflows.

Cross-Functional Delivery

• Partner with AI CoE to consume and operationalize domain models; partner with Agent Engineering and Workflow Integration teams for production implementation.
• Work with Business Translators / Value Assurance to ensure decision products solve the business problem and create measurable impact.
• Create outcome and feedback loops that improve model, workflow and agent behavior over time.

External Relation

• Evaluate relevant GenAI, agentic, workflow and integration technologies based on measurable delivery value rather than novelty.
• Work with technology partners when specialized capability is needed while protecting internal ownership of critical IP and operating knowledge.
• Stay current on agent evaluation, orchestration, safety and production practices.

Qualification:

• Minimum bachelor’s degree in STEM, Statistics, Mathematics, Computer Science, Engineering, Economics or another quantitatively rigorous discipline.
• Experience:
• Minimum 4-8 years across Data Science, applied ML, decision intelligence or AI product development, with evidence of translating analytics into operational actions. Hands-on GenAI / agentic experience is highly desirable.

Skills:

• Strong Python and SQL capability with solid machine learning, statistics, feature engineering and experimentation fundamentals.
• Ability to separate prediction, business policy and workflow orchestration, and to reason about expected value and intervention economics.
• Practical GenAI capability including foundation models, prompting, RAG, structured outputs, function/tool calling and agent orchestration concepts.
• Experience designing API / tool interfaces or working closely with engineering teams to operationalize analytical outputs.
• Understanding of guardrails, human-in-the-loop controls, fallback paths, permissions, evaluation and observability for agentic systems.
• Ability to design experiments and feedback loops that measure intervention and workflow outcomes rather than model metrics alone.
• Strong business translation and communication across technical, product and operational stakeholders.