Operations Research, Senior Data Scientist

AirAsia; Sepang; On-site; MYR 180,000 - 300,000; Full time

Job summary

AirAsia is seeking a Senior Data Scientist (Operations Research) to optimize airline operations using advanced OR techniques. You will model problems, implement mathematical programming, and work with cross-functional teams to translate analytics into value.

The role requires hands-on coding in Python or Go, experience with OR tools, and the ability to deploy scalable solutions in a fast-paced environment. Join AirAsia's Digital & Technology Group to drive data-driven decisions across the

Qualifications

• BS/MS/PhD in Science or related field with strong quantitative focus.
• Experience with data science toolkits, programming languages and databases.
• Applied statistics knowledge for business and finance contexts.

Responsibilities

• Improve models and algorithms to optimize business outcomes.
• Collaborate across teams to understand evolving business needs and implement OR solutions.

Skills

Statistics

Optimization

Python

SQL

Machine learning

Data visualization

Golang

Education

BS/MS/PhD in Statistics/Analytics/AI

Tools

Cplex

Gurobi

OR-Tools

Job description

Senior Data Scientist (Operations Research)

Are you ready to take off and be an Allstar? Whether you’re applying for a developer, customer happiness or crew, at AirAsia we act as One AirAsia.

If you are hungry to make a difference with one of the most well known low-cost airlines and to work in the dynamic technology hub, this is the job for you.

The Data Science Centre of Excellence (CoE) comes under the Digital & Technology Group which is responsible for spearheading digital transformation across AirAsia. The CoE works on business and operations problems across all entities in the AirAsia Group. Key problems we solve include improving revenue and reducing costs through large-scale data federation, predictive and prescriptive analytics, state-of-the-art machine/deep learning, intelligent scheduling and optimization, and other advanced techniques.

Duties and Responsibilities:

• Improve models and algorithms to further optimize business outcomes.
• Collaborate and work across functional and multidisciplinary teams in a dynamic environment to develop an understanding of evolving/agile business needs.

Requirements and Qualifications:

• BS/MS/PhD in Science (Statistics, Management, Cognitive / Psychology, AI, Analytics, Marketing, Design, HCI).
• Up to 8 yrs relevant experience beyond first degree.
• Experience with common data science toolkits, programming languages, visualisation tools and SQL/NoSQL databases.
• Good applied statistical knowledge with emphasis in business and finance related statistical distributions, statistical testing, modeling, regression analysis, etc.
• Experience with distributed computing platforms and open-source tools and libraries.
• Experience developing and deploying to the cloud.
• Familiar or prone to adopt design thinking methods.
• Able to work under pressure and change, and balance among speed, reliability, interpretability.
• Good working knowledge of productivity tools such as G Suite, Git, Jira, Confluence.
• Experience with code versioning, code review and documentation.
• Experience in one or more of the following specialized areas:

Operations Research

• Familiar with modelling problems as mathematical programming, constraint satisfaction, particle swarm optimization and other appropriate OR methodologies.
• Familiar with tools such as Cplex, Gurobi, Google OR-Tools.

Algorithm Engineering

• Strong ability to implement, improve, and deploy ML and Math models in Golang or Python.
• Conduct systems tests for security, performance, and availability.
• Develop and maintain the design and troubleshooting/error documentation.
• Create cost effective scalable systems and develop innovative algorithm solutions.
• Drive decision science aspects as a standard user experience -staff or customer- process (cognitive biases, cross-cultural reasoning, statistical interpretation, human factor impact, algorithmic bias etc.).
• Actively showcase the added value of design thinking, data-driven decisions, agile and user-centric methods.
• Support research (user and markets) and data processes for enhanced decision quality.