Big Data Scientist (Services Analytics)

Quick Facts

• Role: Big Data Scientist (Services Analytics)

• Setting: Agile Scrum, permanent role

Description

Work on analytics capabilities for major customers and aircraft by building and validating data products and models using aircraft sensor, maintenance, and fleet data. You will develop ELT pipelines on big data platforms, conduct exploratory and statistical analysis (including Bayesian inference and anomaly detection), and implement production code mainly in Python. You will present findings to stakeholders and collaborate with cross-functional teams to improve performance and customer experience through digitalization.

Responsibilities

• Ask the right questions to support the discovery process

• Identify data-analytics problems with the greatest organizational impact

• Perform exploratory data analysis with visualization and insights

• Build familiarity with the business and follow market trends

• Present findings to stakeholders using visualization and other communication methods

• Collate and wrangle data: transform, cleanse, and link with other sources

• Prepare datasets for machine/data models and define relationships between data-source attributes

• Apply data-mining techniques and carry out statistical analysis

• Create and validate models, including machine-learning models

• Conduct exploratory analyses, extract content, patch data, and run statistical analysis

• Develop program prototypes and production code, mainly in Python

• Support proof-of-concept execution and ad-hoc requests

• Develop, run, and analyze MCMC simulations

• Drive new working methods and data-governance models

• Share and exchange knowledge; work closely with support and design teams

Requirements

• M.Sc. (ideally a 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 Agile)

• Demonstrated expertise in processing and analyzing aircraft sensor and maintenance data, including ILS or in-service data

• Hands-on experience developing and implementing health-monitoring, predictive-maintenance, or ILS models for aerospace

• Deep knowledge of statistical interpretation and methods (probability distributions, statistical tests, anomaly detection, Bayesian inference)

• Hands-on experience on Big Data projects using Spark and Spark-Submit to build ELT pipelines and data products

• Working knowledge of Unix systems, including command-line operations and Bash scripting

• Production DevOps and Python coding experience; strong SQL and database knowledge

• Experience developing visualization tools such as Spotfire and front-end apps such as Streamlit or Django

• Fluency in English; German is ideally also spoken

Benefits

• Attractive remuneration and additional benefits

• 30 days of annual leave (35-hour week)

• Flexible working arrangements, professional development, and international career opportunities

• Health programs and on-site facilities

• Diverse and inclusive working environment

• Support for customized development and flexible work arrangements wherever possible