(Talent Pool) Data Scientist - Decision Intelligence & Agentic Solutions

PT. Indosat Tbk; Indonesia; On-site; IDR 600,000,000 - 900,000,000; Full time

Job summary

PT. Indosat Tbk in Indonesia seeks a senior Data Scientist to turn analytics into actionable decision workflows and agentic capabilities. You will design deterministic and model-driven decision points, prototype agentic workflows, and measure impact across customer and business outcomes.

Collaborating with the AI Center of Excellence and engineering teams, you will translate complex analytics into practical, scalable decision inputs and guardrails that drive measurable value.

Qualifications

• Bachelor's degree in STEM, Statistics, Mathematics, CS, Engineering, Economics or other quantitative field.
• 4+ years in Data Science, ML, decision intelligence or AI product development with hands-on GenAI experience.
• Proficient in Python and SQL with ML, statistics and experimentation fundamentals.

Responsibilities

• Strategic planning: translate workflows into decision-intelligence use cases with value hypotheses.
• Operational: build analytic components for prediction, prioritization and optimization; expose as inputs for decisions.
• Cross-functional delivery: collaborate with AI CoE, Agent Engineering and Workflow teams for production.
• External relation: evaluate GenAI tech for measurable delivery value and partner with tech vendors.

Skills

Python

SQL

Machine Learning

Decision intelligence

GenAI concepts

Experimentation

Data Science

Communication

Education

Bachelor's degree in STEM or quantitative field

Tools

APIs

Function calling

Retrieval tools

Workflow orchestration

Job description

Role Purpose

• 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.
• Experience designing prioritization, next-best-action, treatment selection, recommendation, optimization or decision-support solutions.
• 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.