Data Scientist AI
Job Description:
Company description:
Airbus pioneers sustainable aerospace for a safe and united world. The Company constantly innovates to provide efficient and technologically-advanced solutions in aerospace, defense, and connected services. In commercial aircraft, Airbus offers modern and fuel-efficient airliners and associated services. Airbus is also a European leader in defense and security and one of the world's leading space businesses. In helicopters, Airbus provides the most efficient civil and military rotorcraft solutions and services worldwide.
Our people work with passion and determination to make the world a more connected, safer and smarter place. Taking pride in our work, we draw on each other's expertise and experience to achieve excellence. Our diversity and teamwork culture propel us to accomplish the extraordinary - on the ground, in the sky and in space.
Founded in 2021, the Airbus Global Business Services (AGBS) unit will be contributing to Airbus’ global success and play a vital role in Airbus’ transformation journey in standardization, harmonization, digitalisation and automation of end-to-end processes (e.g.Procure to Pay) of all overhead functions. Our target is that siloed ways of working / processes will be a relic of the past within the AGBS. To drive such cultural change we are looking for candidates with pioneering spirit that make data-driven decisions and take responsibility for the best outcome of their internal customers. All while embracing a spirit of problem-solving and living the Airbus values: Customer focus, integrity, respect, creativity, reliability and teamwork.
Our purpose defines why we exist: ‘We pioneer sustainable aerospace for a safe and united world’.
Responsibilities - your mission
We are the central Advanced Analytics and Artificial Intelligence team in Airbus for commercial aircraft and we deliver business impact through AI products and services across the entire value chain all the way from selling, designing, procuring, manufacturing to servicing aircraft. As such, we are responsible for solving all aspects and challenges of the machine learning (ML) product lifecycle, including problem exploration, solution development and deployment into cloud native environments at scale.
As part of our team you will work, learn and grow among an international and diverse group of top talent data scientists, software engineers, product managers and many more based across Europe and India. With truly vast amounts of data from all over the Airbus ecosystem at our disposal paired with an unparalleled product complexity, we are exposed to unique and exciting challenges, working at the forefront of AI in the aviation industry.
Key responsibilities for this role include but are not limited to:
Partner with business functions on missions to absorb domain expertise and priorities, build analytical insights and translate business challenges into AI related opportunities that you will tackle with our wider team
Carry out hands-on, end-to-end AI / ML model development from early ideation, exploration and feasibility studies on to design, development, deployment as well as monitoring of scaled AI services
Support our AI capability teams in defining and delivering on AI capability roadmaps (built around 5 technology pillars: computer vision, knowledge extraction, Time-series anomaly detection, decision making and hybrid modeling) that target reusable services and components which are consumed by a wide range of IT products
Representing the central AI organization, evangelize and establish best practices and guidance on delivering and running AI solutions in the rapidly growing Airbus Lisbon office
Engaging in the global AI and analytics community as well as growing the local community footprint, through holding project showcases, sharing expertise as well as best practices
Requirements - our ideal candidate will have
3+ years industry experience in data science, AI or a similar field with a track record of end-to-end model development and handling large data-sets
Strong, fundamental understanding of common ML algorithms
Bachelor’s, Master’s or PhD degree in Computer Science, Data Science, Statistics, Engineering, Mathematics or a related quantitative discipline
Deepened knowledge in at least one of the following fields: NLP, Computer Vision, Time Series Analysis
High Proficiency in Python including relevant open source libraries such as Pandas, Scikit-Learn, Tensorflow and PyTorch
Fluent in written and spoken English
Experience in customer facing roles focused on business impact and managing expectations
Experience in process analysis and process optimization including methodologies such as value stream mapping
Development and deployment of models in cloud environments like AWS, GCP or SAP
Agile and product-oriented development
Benefits - what’s in it for you
Diverse career opportunities within Airbus European core countries or in other regions around the world.
A hybrid working model, allowing you to combine onsite and offsite work.
A modern office at Parque das Nacoes, well connected to public transportation.
A motivated and fun crew to grow and build and shape the GBS together.
An intense and exciting onboarding experience.
This job requires an awareness of any potential compliance risks and a commitment to act with integrity, as the foundation for the Company’s success, reputation and sustainable growth.
Company:
Airbus Portugal SAEmployment Type:
Permanent-------
Experience Level:
Entry LevelJob Family:
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Airbus is committed to achieving workforce diversity and creating an inclusive working environment. We welcome all applications irrespective of social and cultural background, age, gender, disability, sexual orientation or religious belief.
Airbus is, and always has been, committed to equal opportunities for all. As such, we will never ask for any type of monetary exchange in the frame of a recruitment process. Any impersonation of Airbus to do so should be reported to [email protected].
At Airbus, we support you to work, connect and collaborate more easily and flexibly. Wherever possible, we foster flexible working arrangements to stimulate innovative thinking.