At a Glance
- Tasks: Create innovative AI-driven solutions for engineering challenges and collaborate with top industry experts.
- Company: PhysicsX, a deep-tech company revolutionising hardware innovation with AI.
- Benefits: Equity options, generous leave, private medical insurance, and personal development support.
- Other info: Exciting travel opportunities and a flat structure that values your ideas.
- Why this job: Make a real-world impact while working on cutting-edge technology in a collaborative environment.
- Qualifications: Experience in data science, deep learning, and proficiency in Python and relevant libraries.
The predicted salary is between 50000 - 70000 € per year.
About us PhysicsX is a deep-tech company with roots in numerical physics and Formula One, dedicated to accelerating hardware innovation at the speed of software. We are building an AI-driven simulation software stack for engineering and manufacturing across advanced industries. By enabling high-fidelity, multi-physics simulation through AI inference across the entire engineering lifecycle, PhysicsX unlocks new levels of optimization and automation in design, manufacturing, and operations — empowering engineers to push the boundaries of possibility. Our customers include leading innovators in Aerospace & Defense, Materials, Energy, Semiconductors, and Automotive.
Who We're Looking For As a Data Scientist in Delivery, you are a problem solver and builder who is passionate about creating practical solutions that enable customers to make better engineering decisions. You are someone who can grasp advanced engineering concepts across multiple industries, and you excel at working directly with customers (and often side-by-side with them on-site) to transform cutting edge AI models into tools that are useful and used. You’ve worked on difficult problems that require strong foundations in data driven modelling and deep learning techniques, with hands-on experience in probabilistic methods and predictive modelling. Expertise in python, along with proficiency in libraries like NumPy, SciPy, Pandas, TensorFlow and PyTorch, is essential, with the ability to deploy scalable, production-ready models and data pipelines. With at least 1 year industry experience (post Masters or PhD) in a commercial, non-research environment, you’re ready to hit the ground running. You’re truly excited about growing your technical expertise and are naturally inclined to take ownership of data science work streams, continuously improving the systems and solutions you work on to ensure they are practical, impactful and meet the evolving needs of our customers.
This Role In this role, you’ll work closely with our Simulation Engineers, Machine Learning Engineers, and customers to understand and define the engineering and physics challenges we are solving. You’ll build the foundations for successful, impactful solutions by:
- Pre-processing and analyzing data to prepare it for use in predictive modelling, building the foundation for machine learning algorithms to be developed.
- Developing and utilizing innovative deep learning models in combination with state-of-the-art optimization methods to predict and control the behaviour of physical systems.
- Taking full responsibility for the quality, accuracy and impact of your work.
- Designing, building and testing data pipelines that are reliable, scalable and easily deployable in production environments.
- Working closely with simulation engineers to ensure seamless integration of data science models with simulations.
- Contributing to internal R&D and product development, helping to refine models and identify new areas of application.
- Engaging in open communication and presentation with both technical teams and customers, helping onboard users and co-develop with customers.
You'll also have the opportunity to travel to customer sites in North America, Europe, Asia, Oceania, for an average of 3-4 weeks per quarter, where you'll collaborate closely with customers to build solutions on-site. As the role evolves, there are exciting opportunities for growth as an individual contributor or a technical lead, especially if you’re driven by taking ownership of more complex projects and leading the direction of future solutions. Please note, this role is based in London, working 2-3 days per week in our central office.
What we offer Build what actually matters Help shape an AI-native engineering company at a formative stage, tackling problems that genuinely matter for industry and society. This is work with real-world impact - and something you can be proud to stand behind. Learn alongside exceptional people Work with a high-caliber, collaborative team of engineers, scientists, and operators who care deeply about doing great work, and about helping each other get better. We come from diverse backgrounds, but we share a commitment to operating at the highest level and addressing some of the most complex challenges out there. If you’re ambitious, thoughtful, and driven by impact, you’ll feel at home. Influence over hierarchy We operate with a flat structure: good ideas win - wherever they come from. Questioning assumptions and challenging the status quo isn’t just welcomed, it’s expected. Sustainable pace, long-term ambition Building meaningful technology is a marathon, not a sprint. We believe in balancing focused, ambitious work with a life beyond it. Our hybrid model blends time together in our Shoreditch office with work-from-home days, giving you the flexibility to work sustainably while staying connected in person.
We value diversity and are committed to equal employment opportunity regardless of sex, race, religion, ethnicity, nationality, disability, age, sexual orientation or gender identity. We strongly encourage individuals from groups traditionally underrepresented in tech to apply. To help make a change, we sponsor bright women from disadvantaged backgrounds through their university degrees in science and mathematics. We collect diversity and inclusion data solely for the purpose of monitoring the effectiveness of our equal opportunities policies and ensuring compliance with UK employment and equality legislation. This information is confidential, used only in aggregate form, and will not influence the outcome of your application.
Data Scientist in London employer: Physicsx
PhysicsX is an exceptional employer that fosters a collaborative and innovative work culture, where your contributions directly impact real-world engineering challenges. With a strong emphasis on employee growth, you will have the opportunity to learn alongside top-tier professionals while enjoying a flexible hybrid work model in vibrant London. Our comprehensive benefits package, including equity options, generous parental leave, and a commitment to personal development, ensures that you can thrive both professionally and personally.
StudySmarter Expert Advice🤫
We think this is how you could land Data Scientist in London
✨Tip Number 1
Network like a pro! Get out there and connect with people in the industry. Attend meetups, webinars, or even just grab a coffee with someone who works at PhysicsX. Building relationships can open doors that a CV just can't.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving Python, TensorFlow, or any predictive modelling work. This gives potential employers a taste of what you can do and how you tackle real-world problems.
✨Tip Number 3
Prepare for the interview by understanding PhysicsX's mission and the challenges they face. Think about how your experience aligns with their needs and be ready to discuss specific examples of how you've solved similar problems in the past.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows you're genuinely interested in being part of the PhysicsX team and contributing to their innovative journey.
We think you need these skills to ace Data Scientist in London
Some tips for your application 🫡
Show Your Passion:When writing your application, let your enthusiasm for data science and engineering shine through. We want to see that you're genuinely excited about the role and how you can contribute to our mission at PhysicsX.
Tailor Your Experience:Make sure to highlight your relevant experience in data-driven modelling and deep learning techniques. We’re looking for specific examples of how you've tackled complex problems, so don’t hold back on the details!
Be Clear and Concise:Keep your application straightforward and to the point. We appreciate clarity, so avoid jargon and make sure your skills and experiences are easy to understand. Remember, we want to know how you can help us solve real-world challenges.
Apply Through Our Website:We encourage you to submit your application directly through our website. It’s the best way for us to receive your details and ensures you’re considered for the role. Plus, it shows you’re keen to join our team!
How to prepare for a job interview at Physicsx
✨Know Your Stuff
Make sure you brush up on your knowledge of data-driven modelling and deep learning techniques. Be ready to discuss your hands-on experience with Python and libraries like NumPy, SciPy, and TensorFlow. The more you can demonstrate your technical expertise, the better!
✨Understand the Company
Dive into PhysicsX's mission and the industries they serve. Familiarise yourself with their AI-driven simulation software and how it impacts engineering decisions. Showing that you understand their goals will help you stand out as a candidate who is genuinely interested in contributing.
✨Prepare for Problem-Solving Questions
Expect to tackle some challenging problems during the interview. Think about past experiences where you've solved complex issues using predictive modelling or probabilistic methods. Be ready to walk through your thought process and the impact of your solutions.
✨Engage with the Interviewers
Remember, interviews are a two-way street! Prepare thoughtful questions about the role, team dynamics, and how your work will contribute to the company's success. Engaging in open communication will show that you're not just a fit for the role, but also a great cultural match.