Principal Data Scientist

Job Description

Job Title**:Lead/Principal Data Scientist**

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.

Group Data comes under AirAsia Digital which is responsible for spearheading digital transformation across AirAsia. Group Data 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. Group Data is also responsible for the data lakes across all our businesses, deriving insights and value from them and sharing them back with the businesses. In addition, Group Data also actively participates in innovation and training in the Redbeat Academy as well as collaboration with strategic partners like Google, GE, Airbus, and academia.
**Here’s what an ordinary day looks like**:

- You will define, implement and train analytical and statistical advanced models that significantly impact the field of data analytics in areas such as supply chain optimization, resources scheduling, demand forecasting, urban and digital farming, IOT systems, manufacturing optimization, location-based services, business strategy and more.- You will identify requirements, scope your research, identify optimal, problem-specific modelling approaches, develop prototypes, and deliver solutions that directly provide value to the business.
- You will Identify opportunity areas for future improvements (models and algorithms) to further optimize business outcomes.
- You will collaborate, work, build relationships, and communicate across functional and multidisciplinary teams in a dynamic environment to develop an understanding of evolving/agile business needs and to deliver successful solutions.
- You will Keep up with current technical and industry developments.
- You will mentor junior data scientists.

**You got to have these to carry out the job**:

- Experience in problem-solving with an emphasis on business solution product development.
- Hands-on experience in complex data modelling, data analytics, simulation and optimization.
- Experience in developing in-depth analytical understanding of systems.
- Experience in working with large real-world data sets
- Experience in executing critical research and development
- Experience with common data science toolkits, programming languages, visualization tools and SQL/NoSQL databases.
- Good working knowledge of productivity tools such as G Suite, Git, Jira, Confluence.
- Experience in Object-Oriented Programming languages as Java, C++, Python or similar.
- Experience with code versioning, code review and documentation.
- Experience with distributed computing platforms and open-source tools and libraries.
- Experience in developing and deploying to the cloud.
- Experience in working under pressure and change, and balance among speed, reliability, interpretability.

**The job is ideal for you if you have experience in**:
Operations Research- Experience in Large-Scale/Complex Optimization Problems (Resource Scheduling/Planning, Transportation, Supply/Demand Chain Planning and Forecasting, Warehouse Management, Inventory Management, Telecommunication, Network Design, Engineering Design Optimization, etc.)
- Familiar with Linear/Non-Linear Programming, Mixed-Integer Programming and Constraint Programming
- Familiar with Heuristics, Metaheuristics (Simulated Annealing, Particle Swarm Optimization, Tabu search), Large neighborhood search techniques, Multi Agent System and other appropriate OR methodologies.
- Familiar with Cplex, Gurobi, Google OR-Tools, Xpress or similar.

Machine Learning
- Understanding of ML 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 (or AWS/AZURE) products and services such as Vision API, Recommendations API, Cloud Natural Language.
- An in-depth knowledge of AI techniques, their real-world advantages/drawbacks, and ability to prescribe and implement feasible and appropriate conventional/AI related techniques that serve as solutions to problems.

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.
- Research on algorithm improvements for higher performance, accuracy, and optimality.

Decision intelligence
- Drive decision science aspects as a standard user experience -staff or customer
- process
- Actively showcase the added value of design thinking, data-driven decisions,