Big Data Scientist for the Services Analytics Plateau

Airbus; Manching; On-site; EUR 90,000 - 120,000; Full time

Benefits offered by this job

30 days annual leave

Flexitime

Company pension scheme

Bike leasing

Canteen and on-site health facilities

On-site doctor

Job summary

Airbus Defence and Space GmbH in Germany seeks a Big Data Scientist to advance analytics capabilities across multiple data products and use cases. You will develop data-driven solutions, perform exploratory analyses, and present insights to diverse stakeholders.

The role emphasizes Python-based development, ML/AI techniques, data wrangling, and collaboration with cross-functional teams in an Agile setting. Location-based on-site work in Bayern is available.

Qualifications

• M.Sc. (ideally Ph.D.) in statistics, mathematics, computer science, physics, aerospace engineering or a related field.
• Several years of relevant professional experience in data-driven projects, preferably in an Agile environment.
• Experience processing and analyzing Aircraft sensor/maintenance data, or fleet data, including ILS or in-service data.
• Hands-on development of health monitoring, predictive maintenance, or ILS models for aerospace.
• Strong knowledge in data analysis and statistical interpretations (prob distributions, tests, anomaly detection, Bayesian inference).
• Experience in Big Data projects using Spark and Spark-Submit for ELT pipelines and data products.
• Unix systems knowledge with command line and scripting (Bash).
• DevOps and Python coding in production environments; strong SQL/database knowledge.
• Experience with visualization tools (Spotfire) and frontend apps (Streamlit, Django).
• Fluent in English and ideally German.

Responsibilities

• Ask the right questions to support the discovery process.
• Identify data-analytics problems with greatest organizational impact.
• Perform exploratory data analysis using visualization and statistical methods.
• Present findings to stakeholders using visualization and other means.
• Collate data and perform data wrangling (transforming, cleansing, linking).
• Provide datasets for machine learning models and determine relationships between data sources.
• Apply data mining techniques for statistical analyses.
• Create and validate models, including ML-based approaches.
• Develop prototypes and production code in Python.
• Support PoC and ad-hoc requests within the community.
• Develop and handle MCMC simulations and output analysis.
• Drive new data governance methods and working practices.
• Present results to engineers and managers; share knowledge with teams.

Skills

Python

Spark

SQL

DevOps

Unix Bash

Spotfire

Streamlit

Django

English

German

MCMC simulations

Machine learning

Education

M.Sc. (ideally Ph.D.) in statistics/mathematics/computer science/physics/aerospace engineering

Tools

Spotfire

SQL databases

Job description

Job Description: The Services Analytics Plateau (working mode: Agile Scrum) is searching for an experienced Big-Data-Scientist (d/f/m) The project you will be working on represents Airbus Defence and Space's analytics capabilities for our largest customers and all our large aircraft. It delivers improved performance and customer experience and enables a rapid understanding of the potential of digitalization for our customers. You will be at the forefront of further developing our Data Analytics solutions. The main task will be to find new ways to address challenges with data and digital technologies and support the creation of new services. We have well over 100 data products and operate more than 50 use cases in production. In addition, we already have a data pool of several terabytes. This role is also available with reduced weekly hours and an adapted scope of tasks.

Your location

Located about an hour’s drive north of Munich, Manching is an up-and-coming market town that offers a wide range of leisure and cultural activities. Here, you can enjoy the quality of life in the countryside while the pleasures of near-by cities are still within easy reach.

Our Benefits for You

• Fair Compensation & Extras: Attractive remuneration and individual additional benefits, such as company pension schemes, mobility offers (e.g., bike leasing), or corporate discounts with partner companies in accordance with our current guidelines.
• Time for You (and Your Loved Ones): 30 days of annual leave based on our collective agreement (35-hour week); work-life balance through flexible working hours (flextime), mobile working, part-time options, job sharing, and sabbatical opportunities.
• Growth Made Easy: Excellent professional development opportunities and international, group-wide career perspectives.
• Feel Good at Work: On-site company doctor; comprehensive health programs (sports courses, preventive care, etc.), canteen and cafeteria, and local childcare facilities at selected locations.
• Diversity Connects: Work in a diverse environment with more than 140 nationalities, where exchange, mutual support, and inclusion are part of our DNA.

Your tasks and responsibilities

• Ask the right questions to support the discovery process
• Identify the data-analytics problems that offer the greatest opportunities to the organization
• Perform exploratory data analysis using visualization and sense
• You are or will be familiar with our business and actively follow market trends
• You present your findings to stakeholders using visualization and other means
• Collating data and "data wrangling", i.e. transforming, cleansing and linking it with other data.
• Providing data sets for machine data models; determining relationships between data source attributes
• Apply data mining techniques to carry out statistical analysis.
• Create and validate models, also but not only using ML Exploratory analyses of data, extraction of specific content, patching, and statistical analysis
• Develop and implement programm prototypes and production code, mainly in Python
• Supporting the execution of proof-of-concept and ad-hoc requests within the community
• Development and handling of MCMC simulations, as well as output analysis.
• Driving new working methods and new data governance models.
• Presenting results to diverse audiences; from engineers to managers
• Sharing and exchanging knowledge with other teams and working closely with the different support teams, the design office et al.

Desired skills and qualifications

• M.Sc. (ideally Ph.D.) in statistics, mathematics, computer science, physics, aerospace engineering or a related field
• Several years of relevant professional experience working in data-driven projects, preferably within an Agile environment
• Demonstrated expertise in processing and analyzing of: Aircraft sensor and maintenance data, or Aircraft or fleet data, including ILS (Integrated Logistics Support) or in-service data
• Hands‑on experience in the development and implementation of health monitoring, predictive maintenance, or Integrated Logistic Support (ILS) models for the aerospace sector
• Deep knowledge and expertise in data analysis and statistical interpretations of data (e.g. probability distributions, statistical tests, anomaly detection, Bayesian inference)
• Experience working in Big Data Projects using Spark and Spark-Submit Jobs for building ELT pipelines and creating data products
• Working knowledge of Unix systems, including command line operations and scripting (e.g., Bash)
• Expertise in DevOps and Python coding in a production environment, as well as excellent knowledge of SQL technologies and databases
• Experience in the development of visualization tools (e.g. Spotfire) and front‑end applications (Streamlit, Django)
• Fluent in English and ideally also in German

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 Defence and Space GmbH Employment Type: Permanent ------- Experience Level: Professional Job Family: Configuration Management

Airbus is, and always has been, committed to equal opportunities for all.

We welcome all applications irrespective of social and cultural background, age, gender, disability, sexual orientation or religious belief.