At McLaren Racing, we believe only by chasing performance in everything we do can we give ourselves the best chance of success. Performance on track and in the factory. Performance for our people, our business and our partners. It’s about more than winning. It’s about hitting the highest standards, and then raising the bar again.
Purpose of the Role:
The purpose of this role is to use approaches and techniques from the field of Data Science to unlock new insights from our data, improve our effectiveness in car development and, ultimately, drive our performance forward on track.
Role Context:
This role lies within the Data Science team, which is part of the Software & Data Science department. This team is responsible for all data science, AI, and machine learning tools and techniques across the whole of F1. This means working with all modes of data, for example: tabular, time series, images, video, text, and audio. The team works with stakeholders from across Racing to understand and exploit opportunities.
Role Description:
As a Specialist, Data Science you will have a firm foundation of experience and knowledge in data science, in particular, in implementing machine learning algorithms on real world problems. You will use this to develop innovative, data-driven solutions to technical challenges alongside senior members of the team. This will involve exploring complex datasets, developing models and processing algorithms, evaluating their success, and creating deployment pipelines.
You will work on projects through all stages of the development life cycle from initial analysis and requirements gathering through to deployment and operational support. Your work will be a mixture of longer-term development projects and operational support of tools already in production. You will work in close cooperation and co-development with the other members of the team, as well as stakeholders across Engineering. Hence, you should be comfortable both working on a project by yourself and jointly with others.
You should be capable of managing a project assigned to you, tracking and reporting on your tasks, time, and resources to help deliver work that meets the requirements on time.
You need a keen desire to continue learning software development and data science, following the department’s guiding principles, and a passion to use your skills to make the car faster.
The flexibility to work out of office hours and weekends as the needs of the team require may be needed.
Principal Accountabilities:
- To take and understand project requirements to define specifications and to architect robust, scalable and testable software and data science solutions.
- To confidently analyse and overcome technical challenges with workable and innovative solutions.
- To understand the processes and goals underlying the various technical areas you work alongside.
- Business analysis of aerodynamic development processes including understanding the goals, the current problems, and then sharing your learning with the team.
- Development of analytical solutions to complex engineering problems using leading edge data science, modeling, and optimisation techniques.
- To maintain consistent standards and approaches adopted by the team.
- To accurately estimate activity timescales and provide regular progress reports.
- To efficiently manage your workload.
- To raise awareness of and mitigate against potential technical risks.
Knowledge, Skills and Experience:
Essential
- Strong academic background with undergraduate or postgraduate degree in relevant discipline or equivalent industry experience
- Previous experience in a Python-based data science role
- Knowledge of data science algorithms and techniques from several areas such as regression, classification, time series modelling, optimisation, computer vision, and unsupervised learning
- Able read and then discuss an academic research paper with senior members of the team before implementing a data science algorithm from it in Python.
- Experience with advanced data exploration techniques to understand underlying behaviour.
- Effective communication, both written and verbal .
Desirable
- Skilled with Python data science packages, including sklearn and PyTorch/Keras/TensorFlow.
- Experience in the analysis of complex data sets to understand underlying behaviour.
- Familiarity with object-oriented programming and development of large software projects.
- Experience with MLOps, development and production pipelines and deployment frameworks.
- Previous use of Docker and Kubenetes would be an advantage
- Some knowledge of web development techniques or of dashboarding libraries such as Streamlit.
- Basic knowledge of vehicle dynamics / aerodynamics and the development processes employed within F1.
Personal Attributes:
- Enthusiasm for engineering and science.
- Ability to work to tight deadlines.
- Open mindedness to ensure high flexibility and the capacity to manage rapid and profound changes of scopes, development directions and processes.
- Aptitude to learn from others and share knowledge with others.
What can McLaren offer?
We constantly strive to be better tomorrow than we are today. Our ambition is to be the most pioneering and exhilarating racing team in the world, and our collective task is to set the standards for high performance in sport. We show up every day with energy and enthusiasm, ready to play our part.
We encourage and support diversity, equity and inclusion. We will actively promote a culture that values difference and eliminates discrimination in our workplace.
McLaren Racing is based at the iconic McLaren Technology Centre (MTC) near Woking. Our state of the art, sustainable campus offers many facilities including a gym, restaurant and indoor and outdoor break-out areas, as well as direct access to park and common land. The MTC is connected to Woking mainline station via regular fully-electric shuttle buses, from which London Waterloo is a 30 minute train ride.
Hybrid working patterns give you options to balance your home life and outside interests with your work. We offer a comprehensive package of benefits including private healthcare, car schemes, life insurance and generous pension contributions.