Senior/Data Scientist - Flight

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Job ID: MJ000382About the TeamThe Flight & Platform Data team turns Traveloka’s data into insights and intelligent solutions that improve how our business and system operate. We partner with Product and Engineering teams to solve business problems through data science, experimentation and automation.About the RoleTraveloka is seeking a hands-on Senior Data Scientist to build data science solutions and LLM-powered agents.You will connect business problems with the data, models and workflows needed to solve them. This includes understanding how data moves from source systems through ingestion, transformation and storage into analytical datasets, models and agent applications.A central part of your role will be building agents that can access relevant business data, use tools and produce reliable outputs—for use cases such as investigating supply anomalies, automating recurring analysis and generating actionable commercial insights.Working closely with data and engineering teams, you will take solutions from problem definition through development, evaluation, rollout and improvement.What You’ll DoBuild LLM-Powered Agents: Design and develop agents that support business workflows. Connect LLMs with business datasets, APIs and analytical tools through retrieval, tool calling and workflow orchestration.Work Across the Data Lifecycle: Understand source systems and downstream dependencies; work with data engineers to develop reliable transformations, analytical datasets and features. Ensure the data feeding models and agents is accurate, timely and fit for purpose.Evaluate and Improve Agent Reliability: Define evaluation datasets, success criteria and business-rule checks. Investigate incorrect outputs, retrieval gaps and tool failures, and improve performance through systematic testing and iteration.Develop Models for Business Decisions: Apply forecasting, anomaly detection, simulation and causal inference to problems involving supply pricing, inventory quality and commercial performance. Estimate expected outcomes and measure actual impact against appropriate baselines.Deliver and Maintain Usable Solutions: Partner with engineering teams to integrate models and agents into business workflows. Monitor data quality, solution performance and user feedback, and resolve issues across the data-to-output flow.Automate Analytics and Strengthen Measurement: Replace repetitive reporting and investigation tasks with reusable workflows. Establish trusted KPIs and measurement frameworks, using dashboards and reports where they help stakeholders act on findings.What You’ll Bring5+ years of relevant experience in data science, applied machine learning or a related technical field, with demonstrated ownership of data-driven solutions.Hands-on experience building LLM-powered agents or applications with agent capabilities, such as retrieving information, calling tools or APIs, querying structured data, or executing multi-step workflows. You can explain the architecture, your implementation contributions and how you evaluated the outputs.Strong understanding of end-to-end data flows, including ingestion, transformation, storage, data modeling and consumption by downstream applications. You can trace data dependencies and investigate quality issues across these stages.Strong Python and advanced SQL skills, with experience writing reusable code for data processing, modeling, integrations and automation.A solid foundation in statistics and applied modeling, with practical experience in areas such as forecasting, anomaly detection, experimentation, simulation or causal inference.An evaluation mindset: you define what success looks like, test assumptions, investigate failure cases and connect technical performance with business outcomes.Strong business judgment and communication skills, with the ability to frame ambiguous problems, explain trade-offs and work independently with commercial, product and engineering stakeholders.It’s a Plus If You HaveExperience deploying and monitoring models or LLM agents used in live business workflows.Experience building ETL/ELT pipelines, reusable data assets or data-quality checks.Experience in travel, airlines, e-commerce or marketplaces, particularly pricing, revenue management or supply optimization.Experience with agent-development frameworks, retrieval systems, evaluation tools or observability platforms.