What To Expect
As a Data Scientist, you will work closely with engineering teams to develop models that support design, testing, and operational decision‑making. This includes building and validating models such as battery lifespan predictions and surrogate models for loads modelling. You will be expected to take problems from concept through to deployable solutions, working with data engineers to ensure models are supported by reliable data pipelines and can be integrated into engineering workflows. The role requires a strong focus on practical application, ensuring models are interpretable, validated, and usable within a certification‑driven environment.
What You’ll Do
- Develop and validate predictive models to support a range of engineering and operational use cases, including performance forecasting and reliability analysis
- Build surrogate and approximation models to represent complex systems and simulations, enabling faster and more scalable analysis
- Work closely with engineering teams to understand physical systems and translate them into data‑driven models
- Analyse large‑scale time‑series datasets from flight and test environments
- Collaborate with data engineering to ensure reliable data ingestion, transformation, and availability for modelling to enable data science and advanced analytics
- Deploy models into production environments or engineering toolchains, ensuring they are maintainable and usable
- Ensure models are well‑documented, explainable, and aligned with engineering and certification requirements
- Contribute to the development of reusable modelling frameworks and approaches across the organisation
- Support the wider analytics capability where advanced modelling or statistical analysis is required
What You’ll Bring
- Strong experience in applied data science or scientific modelling within an engineering or physical systems context
- Proven ability to develop, validate, and deploy predictive models using real‑world data
- Experience working with time‑series data and sensor‑driven datasets
- Solid understanding of statistical methods, machine learning techniques, and model validation approaches
- Experience working in Python or similar, with relevant scientific and data libraries
- Ability to work closely with domain experts (e.g. aerospace, mechanical, or electrical engineers) and translate requirements into models
- Understanding of the challenges of deploying models into production or engineering environments
- Strong problem‑solving skills, with a focus on practical and usable outputs rather than theoretical models
- Interest in aviation, electric propulsion, or complex engineered systems
Our Benefits
- 26 days holiday, plus bank holiday
- 5 extra days per year to buy (or sell)
- 5 extra days holiday when you get married or enter a civil partnership
- Additional 4% of your salary to spend on extra benefits
- Award‑winning digital health and wellbeing service (Help@Hand)
- Company performance based bonus – rewarding company and individual performance
- Company Share Scheme – open to every Vertical employee
- Company Pension Scheme – 5% and we match it
- Breakfast on us, every day
Disclaimer Statement
We encourage you to apply even if you may not have all the experience listed in the advert. We recognise that talent comes in various forms and we are committed to providing opportunities that create an environment of growth, diversity, and inclusion for everyone. As part of our desire to review and make our processes fair, we may ask you questions related to these aspects during the application process. For more information on how we will use your data, see our Legal section.
#J-18808-Ljbffr…