Qantas Airways

4 weeks ago

Operational Research Manager

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 23 hours agoStatus: Live

Job Summary

Lead the design and deployment of advanced decision-support models (optimisation, simulation, predictive) for Jetstar Operations Control Centre, partnering with Technology, Data & Analytics to productionise models that improve performance, cost efficiency, and decision-making at scale.

Location: Melbourne

Workplace: Onsite

Employment Type: Full time

Job Function: Research & Scientific (R&D)

Seniority: Mid level

Key Responsibilities

•Lead the design and evolution of optimisation, simulation and predictive models (e.g. tail assignment, recovery, delay prediction).
•Own the end-to-end model lifecycle, from problem framing through to deployment including defining system architecture, building validation and testing frameworks, and establishing logging and monitoring for production models.
•Build a connected suite of models where outputs inform downstream decisions, progressing toward a network digital twin.
•Ensure models are robust, auditable and trusted through strong validation, documentation, and performance frameworks.
•Drive adoption by embedding model outputs into JOCC workflows and decision-making processes.

Pay and Benefits

Perks:Travel Allowance

Key Requirements

•Experience building and deploying decision-support models (optimisation, simulation, predictive) in production environments.
•Hands-on experience with mathematical optimisation solvers (e.g. Gurobi, CPLEX) including formulating MIP, LP, or CP models from scratch.
•Strong Python engineering skills including model productionisation, API design, and deployment infrastructure (e.g. Docker, containerised workers, REST APIs).
•Strong software engineering capability within OR — comfortable owning the full stack from model logic through to deployed systems.
•Experience working with cloud data platforms (e.g. Snowflake or similar).

Experience:Airlines/aviation

Skills:LeadershipStakeholder managementCommunicationProblem-solving

Languages:English

Tech Stack:PythonGurobiCPLEXDockerREST APISnowflake

Company Brief

Qantas Airways

Australia’s flag carrier providing domestic, international and freight air services, operating Qantas, Jetstar and QantasLink brands, plus a loyalty business (Qantas Frequent Flyer) and aviation services.

Industry: Airlines

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: Mascot, NSW, Australia

Founded: 1920

Glassdoor: 3.8

Website LinkedIn Glassdoor

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Qantas Airways

4 weeks ago

Operational Research Manager

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 23 hours agoStatus: Live

Job Summary

Location: Melbourne

Workplace: Onsite

Employment Type: Full time

Job Function: Research & Scientific (R&D)

Seniority: Mid level

Key Responsibilities

•Lead the design and evolution of optimisation, simulation and predictive models (e.g. tail assignment, recovery, delay prediction).
•Own the end-to-end model lifecycle, from problem framing through to deployment including defining system architecture, building validation and testing frameworks, and establishing logging and monitoring for production models.
•Build a connected suite of models where outputs inform downstream decisions, progressing toward a network digital twin.
•Ensure models are robust, auditable and trusted through strong validation, documentation, and performance frameworks.
•Drive adoption by embedding model outputs into JOCC workflows and decision-making processes.

Pay and Benefits

Perks:Travel Allowance

Key Requirements

•Experience building and deploying decision-support models (optimisation, simulation, predictive) in production environments.
•Hands-on experience with mathematical optimisation solvers (e.g. Gurobi, CPLEX) including formulating MIP, LP, or CP models from scratch.
•Strong Python engineering skills including model productionisation, API design, and deployment infrastructure (e.g. Docker, containerised workers, REST APIs).
•Strong software engineering capability within OR — comfortable owning the full stack from model logic through to deployed systems.
•Experience working with cloud data platforms (e.g. Snowflake or similar).

Experience:Airlines/aviation

Skills:LeadershipStakeholder managementCommunicationProblem-solving

Languages:English

Tech Stack:PythonGurobiCPLEXDockerREST APISnowflake

Company Brief

Qantas Airways

Industry: Airlines

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: Mascot, NSW, Australia

Founded: 1920

Glassdoor: 3.8

Website LinkedIn Glassdoor