Employment Type: Permanent
Contract Duration:
Why you will love working here
At IATA, we represent over 350 airlines worldwide, striving to make
aviation safer, smarter, more sustainable, and inclusive.
• Our Values are not just words on a page - they are the energy behind everything we do: ONE IATA - We collaborate across teams, TRUSTED - We do the right thing, INNOVATIVE - We make tomorrow better, INCLUSIVE - We embrace diverse perspectives.
• With over 30,000 courses available, we believe in continuous learning and support your growth in an ever-changing industry.
• Diversity, equity, and inclusion are our priorities. We are certified by the Equal Salary Foundation, offering equal pay and family-friendly policies.
• We encourage community involvement through volunteering and strive to make tomorrow better for aviation and our communities. We offer time off so you can support causes important to you.
• We promote work-life balance with flexible work options, including remote and hybrid work, a generous 'work from abroad' policy, and you get your birthday off!
About the team you are joining
The Data Scientist
will be responsible for independently
delivering well-scoped data science solutions, potentially involving multiple
business areas, under the guidance of senior data science and domain leads. Working under the guidance of senior team
members, the role focuses on turning clarified use cases into robust,
production‑ready analytical or machine‑learning solutions. The ideal candidate should have a strong understanding
of statistical modelling, machine learning, and data analysis techniques. They
will work closely with stakeholders across IATA to identify opportunities and
deliver data science projects from initial concept through to successful implementation.
What your day would be like
Reporting to the Head Data Science, you will be an integral part of the Data Science
team, collaborating with the organisation’s Data team to develop machine
learning models and solutions to address complex business challenges.
Work directly with business stakeholders to clarify
requirements, assess feasibility, and translate needs into concrete analytical
or modelling tasks, seeking senior guidance when decisions have wider
architectural or organisational impact.
Take ownership of well‑scoped data science use cases, from
problem refinement and data exploration through to model development,
validation, and handover.
Select appropriate technical methods and tools, balance quality,
feasibility, and timelines, and escalate broader architectural choices when
needed.
Coordinate contributions from team colleagues to keep scoped
projects on track, proactively identifying risks, blockers, and dependencies
and with the wider technical teams to ensure solutions align with best
practices, operational requirements, and team standards.
Communicate progress, insights, and next steps to stakeholders
in a clear, structured way, with support for complex, sensitive, or cross‑team
communication.
Contribute, when appropriate, to data science and AI
communities, as well as governance
activities.
We would love to hear from you if
A master’s degree in data science, mathematics, engineering,
physics, or a related field.
Strong
quantitative, statistical, and programming skills are required, along with
experience in data analysis and machine learning model development.
3+ years
of experience
in Data Science or equivalent work experience in advanced ML, time series or
deep learning algorithms for regression, classification, forecasting and/or clustering problems.
Experience with natural language processing
techniques (NLP) and Generative AI.
Good understanding of deep learning techniques
and frameworks.
Experience with cloud-based machine learning
services such as GCP Vertex AI, AWS
SageMaker and/or Snowflake is an advantage.
Familiarity with Agile development, and data or ML engineering experience is an
advantage.
Travel Required: N
Learn more about IATA’s role in the industry, our benefits, and the team at iata/careers/. We are looking forward to hearing from you!
