About the role:
As a System Controller - Data Scientist, you will be responsible for helping us achieve this ambition through:
Driving innovation by solving key business problems with advanced data analytics and AI. Experimenting with new technologies and concepts to deliver a real positive impact on the airport and its stakeholders. Enabling HIA to continuously perform as a data driven organization.
Operational
Collaborate with business teams to understand company needs and identify machine learning and artificial intelligence use cases across the airport business.
Build custom models and machine-learning algorithms to apply to business-related data sets.
Identify valuable data sources and analyze them to reveal trends, patterns and business insight.
Develop data pipelines for processing of structured and unstructured data.
Use a working knowledge of various AI capabilities such as computer vision, NLP, machine learning to build applications to solve real world problems.
Generate hypotheses and design experiments that deliver tangible business benefits.
Develop testing frameworks to measure model performance pre and post production deployment.
Coordinate the implementation of the model with manager and measure/monitor the outcomes.
Acquire and transform data from source systems in line with business priorities, solving for the key challenges of big data volume, variety, velocity and veracity.
Perform analysis to generate insights for key business challenges or objectives.
Oversee the preparation of technical documentation to ensure adequate data lineage, governance and compliance with information, security and other relevant policies.
Solution Design & Delivery
Facilitate gathering and documenting requirement and business objectives for advanced analytics.
Design, communicate and negotiate technical solutions and implementation plans with various stakeholders.
Deliver committed projects and tasks using agile software delivery methodology.
Contribute to the evaluation and procurement process for data related technologies or COTS systems/products to meet business objectives.
Assist the team to ensure regular compliance with change and other relevant processes of ISO
Conduct root cause analysis of reported incidents in operational systems and ensure right changes to code, test and promote fixes following the established incident management process based on ITIL.
Drive awareness Data Science & Artificial Intelligence capabilities and limitations and develop training content for business users to enhance the Date Culture and Data Literacy.
Drive the usage and adoption of the Business Intelligence Self Service platform.
Qualifications
About you:
Minimum 5 years experience in Data Analytics.
Degree in Computer Science, Mathematics, Engineering or equivalent quantitative discipline.
Qualifications and certifications related to Statistics, Data Science or AI are preferred.
Airport domain experience is preferred but not essential.
Experience of working in an agile delivery environment (user stories, back log grooming, sprints, etc)
Experience of using software to plan, track and manage user stories e.g. JIRA
Sound knowledge of statistics, data profiling, data quality measurement and cleaning.
Skilled at presenting, data storytelling and explaining technical concepts to non-technical audiences.
Adept at generating hypotheses, designing experiments and measuring performance.
Some exposure to Deep Learning, Computer Vision or Reinforcement Learning is advantageous.
Fair knowledge and experience of using of either Python (preferred) or R programming language for analysis and machine learning.
Hands on experience of ML frameworks and toolkits (e.g. Tensorflow, PyTorch, Keras, scikit-learn etc.)
Experience of using code repository and version control software (e.g. Github, BitBucket, TFS, etc.)
Good knowledge of data warehousing concepts and ability to query data using SQL.
Capable of understanding API documentation and querying them using tools such as Postman
Strong exploratory analysis skills with experience using Business Intelligence tools such as PowerBI (preferred), Tableau, SSRS, Qlikview.
Good awareness of Big Data systems and cloud technologies, particularly Azure.
Awareness of DevOps and CI/CD principles.
