At a Glance
- Tasks: Lead data-driven projects, develop AI solutions, and empower engineers with insightful analytics.
- Company: Join JLR, a leader in innovative automotive engineering focused on creating exceptional driving experiences.
- Benefits: Enjoy hybrid working options, award-winning training, and a culture that values diversity and inclusion.
- Why this job: Shape the future of motoring while collaborating with industry experts in a dynamic environment.
- Qualifications: Extensive experience in AI, strong math skills, and proficiency in SQL and Python required.
- Other info: Open to applicants from all backgrounds; growth and development are encouraged.
The predicted salary is between 43200 - 72000 £ per year.
Product Engineering at JLR is centred on innovation and creativity. From advanced driver assistance systems to developing the future of electric propulsion, the opportunities to create exceptional experiences for the future of motoring are wide-ranging. You will work alongside industry experts to drive product strategy, manage programs, analyse performance, and lead transformation initiatives.
WHAT TO EXPECT
Push the boundaries as a Lead Data Scientist within JLR's Body Chassis Engineering (BCE). The Data Analytics Chapter in BCE aims to empower engineers to make data-driven decisions by providing accessible, reliable data and delivering insightful analytics to squads across the organisation. The team develops methods and tools that leverage the data collected off Fleet and Customer vehicles, supporting improvements to Body/Chassis features and systems that will ensure an exceptional experience for JLR's customers.
In this role, you will play a key part in shaping the AI & Data Science capabilities of the team. You will use advanced techniques to generate insights into our systems and how customers operate their vehicles, across a variety of use cases. You will lead the development of new methods and tools, promote best practice techniques and continuous improvement, and work closely with the Chapter Lead to develop others.
Key Accountabilities and Responsibilities
- Understand data requirements of stakeholders, including problem scoping.
- Use statistical techniques to deliver robust and accurate results, considering variable data quality, and clearly communicate conclusions and insights to stakeholders.
- Algorithm development and selection, as well as model training, evaluation and monitoring.
- Ensure customer privacy is protected at every stage of data analysis.
- Contribute to knowledge sharing and the continual improvement of the team's technical capabilities, and collaborate with the wider JLR data community to ensure the team works with the latest technology, techniques and best practices.
WHAT YOU'LL NEED
- Extensive experience in ideating, leading, developing and deploying AI & data science solutions that have delivered tangible business value.
- Strong math, statistics and probability skills, with a strong level of ability to structure, analyse and interpret data.
- Competent with SQL and Python, and use of Jupyter Notebook environment (or similar).
- Strong understanding of machine learning techniques such as time series modelling, regression, classification, clustering and anomaly detection.
- Capable of explaining data science concepts and results to non-technical business stakeholders and decision makers.
Creating Modern Luxury requires a modern approach to work. At JLR, hybrid working is a voluntary, non-contractual arrangement providing employees more choice and flexibility around how, when and where they work. Some roles require more on-site work, but details of this can be discussed with the hiring manager during the interview stage.
We work hard to nurture a culture that is inclusive and welcoming to all. We understand candidates may require reasonable adjustments during the recruitment process. Please discuss these with your recruiter so we can accommodate your needs. Applicants from all backgrounds are welcome. If you're unsure that you meet the full criteria of a role – but you're interested in where it could take you – we still encourage you to apply. We believe in people's ability to grow and develop within their role – it's what makes living the exceptional with soul possible.
JLR is committed to equal opportunity for all.
At JLR we are passionate about our people. They are at the heart of our business. We are committed to fostering a diverse, inclusive culture that is representative of our global customers and the society in which we live; a culture in which every one of our employees can bring their authentic self to work, and reach their full potential.
Lead Data Scientist employer: Jaguar & Land Rove
Contact Detail:
Jaguar & Land Rove Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Lead Data Scientist
✨Tip Number 1
Familiarise yourself with JLR's current projects and innovations in data science and AI. Understanding their specific challenges and goals will help you tailor your discussions during interviews, showcasing how your skills can directly contribute to their objectives.
✨Tip Number 2
Network with current or former employees of JLR, especially those in the Data Analytics Chapter. Engaging with them can provide valuable insights into the company culture and expectations, which can be beneficial when preparing for interviews.
✨Tip Number 3
Brush up on your technical skills, particularly in SQL and Python, as well as machine learning techniques relevant to the role. Being able to demonstrate your proficiency in these areas during technical discussions will set you apart from other candidates.
✨Tip Number 4
Prepare to discuss your previous experiences where you've successfully led data science projects that delivered business value. Be ready to explain your thought process, the methodologies you used, and the impact of your work, as this will resonate well with the hiring team.
We think you need these skills to ace Lead Data Scientist
Some tips for your application 🫡
Understand the Role: Before applying, make sure you fully understand the responsibilities and requirements of the Lead Data Scientist position at JLR. Tailor your application to highlight how your skills and experiences align with their needs.
Highlight Relevant Experience: In your CV and cover letter, emphasise your extensive experience in AI and data science solutions. Provide specific examples of projects where you've delivered tangible business value, particularly those involving SQL, Python, and machine learning techniques.
Communicate Clearly: Since the role involves explaining complex data science concepts to non-technical stakeholders, ensure your application demonstrates your ability to communicate insights clearly. Use straightforward language and avoid jargon where possible.
Showcase Continuous Improvement: Mention any initiatives you've led or participated in that focus on continuous improvement and knowledge sharing within a team. This aligns with JLR's emphasis on collaboration and technical capability enhancement.
How to prepare for a job interview at Jaguar & Land Rove
✨Showcase Your Technical Skills
As a Lead Data Scientist, you'll need to demonstrate your extensive experience with AI and data science solutions. Be prepared to discuss specific projects where you've used SQL, Python, and machine learning techniques. Highlight how your contributions delivered tangible business value.
✨Communicate Clearly with Stakeholders
You'll be required to explain complex data science concepts to non-technical stakeholders. Practice articulating your insights in a way that is accessible and engaging. Use examples from your past experiences to illustrate how you effectively communicated findings and influenced decision-making.
✨Emphasise Collaboration and Knowledge Sharing
JLR values teamwork and continuous improvement. Be ready to discuss how you've collaborated with others in the past, particularly in sharing knowledge and best practices. Mention any initiatives you've led or participated in that fostered a culture of learning within your team.
✨Prepare for Problem-Solving Scenarios
Expect to face questions that assess your problem-scoping abilities and statistical analysis skills. Prepare to walk through your thought process on how you would approach a given data challenge, including how you would ensure data quality and protect customer privacy throughout your analysis.