As an Assistant / Principal Data Scientist, you will play a pivotal role in driving our analytics strategy and execution. You will harness advanced data analytics, machine learning, and statistical modelling techniques to provide actionable insights that enhance our operational efficiencies and contribute to our mission of delivering excellence in aerospace solutions. This position offers a unique opportunity to solve complex problems and design analytical models that support strategic decision making across various departments.
Key Responsibilities
- Lead and collaborate with a team of data scientists and analysts, fostering a culture of innovation and continuous improvement.
- Design and implement robust data models and algorithms using advanced statistical techniques.
- Collaborate with cross-functional teams to identify key business challenges and provide data-driven recommendations.
- Develop dashboards and visualisations to communicate findings effectively to stakeholders at all levels.
- Stay abreast of industry trends and advancements in data science to enhance technical knowledge and apply the latest methodologies.
- Contribute to the development of best practices in data governance and data quality management.
Required Skills & Qualifications
The ideal candidate will possess a strong background in a quantitative field such as Data Science, Statistics, Computer Science, or a related discipline, complemented by extensive experience in a data analytics or data science role, preferably within an aerospace or engineering context.
- A Master's degree or PhD in Data Science, Statistics, Machine Learning, or related field.
- Proficient in programming languages such as Python, or SQL, along with experience in machine learning libraries and frameworks.
- Demonstrated ability to manage multiple projects simultaneously and deliver results in a fast-paced environment.
- Strong problem-solving skills and a passion for unraveling complex datasets.
- Excellent communication and interpersonal abilities, with the proficiency to explain complex concepts to non-technical audiences
- Familiarity with aerospace systems (e.g., PLM, MES, MRO platforms) and cloud platforms (e.g., AWS) are advantageous
