Data Scientist

Key Skills

Java Programming, Design, Python Programming, Database, SQL, Git, Machine learning techniques, JIRA, Natural Language Processing (NLP), NoSQL, PyTorch, TensorFlow, Scikit-learn, Naive Bayes, Algorithms, Data Modelling, VR/AR frameworks

Job Description

AirAsia Berhad: Asia’s leading airline was established with the dream of making flying possible for everyone. Since 2001, AirAsia has swiftly broken travel norms around the globe and has risen to become the World’s Best Low-cost Airline by Skytrax, for 11 consecutive years. Driven by the Dare to Dream spirit, we pride ourselves in being the region’s largest low-cost carrier, serving 25 countries and over 140 destinations. As we embrace new technology to become a digital travel company, we seek highly talented individuals to join us on our mission to make AirAsia a part of everyone’s travel and lifestyle.

This position reports into the Data Science Centre of Excellence.

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.

Notes:

• Applications without a proper curriculum vitae will not be considered.
• Fresh graduates without relevant coursework and project work will not be considered.
• A MS or PhD is strongly preferred for Senior, Lead/Manager, Principle/Senior-Manager roles.
• Applicants with experience using Google Cloud Platform are highly favored.
• Only shortlisted candidates will be notified.

Experience

• 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.
• Familiar or prone to adopt design thinking methods.
• Able to operate 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.
• Improve models and algorithms to further optimize business outcomes.
• Experience developing and deploying to the cloud.
• Collaborate and work across functional and multidisciplinary teams in a dynamic environment to develop an understanding of evolving/agile business needs.

Experience in one or more of the following specialized areas:

Machine Learning

• Understanding of machine learning algorithms such as k-NN, Naive Bayes, SVM, Decision trees.
• Experience using ML frameworks such as TensorFlow, PyTorch, or scikit-learn.
• Experience with Google Cloud Platform products and services such as Vision API, Recommendations API, Cloud Natural Language.

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.

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.

Decision intelligence

• 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.

Qualifications

• Data speciality: BS/MS/PhD in a Mathematics, Science or Engineering disciplines.
• Decision science speciality: BS/MS/PhD in science (statistics, management, cognitive/psychology, AI, analytics, marketing, design, HCI)