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- Tasks: Lead the evolution of a groundbreaking statistical model that drives business decisions.
- Company: Join a high-growth tech company with a focus on innovation and impact.
- Benefits: Fully remote work, competitive salary, and the chance to shape your team and projects.
- Why this job: Make a real impact by modelling how people make decisions for top global companies.
- Qualifications: Deep statistical knowledge, Python proficiency, and experience with complex datasets.
- Other info: Opportunity to grow in a dynamic environment with a hands-on leadership role.
The predicted salary is between 48000 - 72000 £ per year.
This is not a role for someone looking to tune hyperparameters on a well-worn stack. This is a role for someone who wants to take ownership of a statistical model that sits at the heart of a high-growth business. A model that doesn’t support the product it is the product.
At its core, the platform simulates how real people make decisions. It ingests vast amounts of historical transactional data and uses this to build millions of virtual customers with unique preferences. These simulations are then used to answer high-stakes commercial questions for some of the largest companies in the world. What happens if we change this product line, raise this price, shift this promotion, the answers aren’t approximated. They’re modeled, tested and surfaced in real-time.
This role is about taking full ownership of the model that makes this possible. You will lead its evolution, challenge its limits, and shape its next chapters. You will not be handed a roadmap. You will help define it. You will work closely with deeply technical founders to explore what is economically and technically possible, and you will be expected to break down complex ideas into workable solutions for your team.
This is a hands-on leadership role. You’ll be growing and leading a team, but you’ll also be deeply involved in the work experimenting with new techniques, exploring new data sources, and constantly refining the engine under the hood. The function today is lean and highly capable, and you’ll have the chance to shape both the model and the team as it scales.
FULLY REMOTE, ANYWHERE IN EUROPE.
What You’ll Need:
- Deep statistical understanding, particularly in classical methods
- Strong proficiency in Python, including experience with ML frameworks like PyTorch
- Strong grasp of linear algebra and numerical modeling techniques
- Experience training models on large, complex datasets
- A scientific mindset and the ability to question assumptions with rigor
- The ability to communicate complex technical ideas in simple, direct terms
- Curiosity about how people make decisions and a desire to model reality, not just predict outcomes
- Integrity and self-awareness knowing what you know, and being honest about what you don’t
- A proven track record of building things that work, and improving things that didn’t
- Experience building foundational or category-specific models is a plus
If you are looking for a role where you can lead technically, challenge intellectually, and contribute directly to the direction of a product used by some of the most recognizable names in global business, this is that role. The impact is tangible. The complexity is real. And the opportunity to shape something meaningful is right in front of you.
Equal Employment Opportunity
We are an equal opportunities employer and welcome applications from all qualified candidates.
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Head of Machine Learning employer: LinuxRecruit
Contact Detail:
LinuxRecruit Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Head of Machine Learning
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect on LinkedIn. We all know that sometimes it’s not just what you know, but who you know that can get you in the door.
✨Tip Number 2
Show off your skills! Create a portfolio or GitHub repository showcasing your projects and models. We want to see your hands-on experience and how you tackle real-world problems, especially with complex datasets.
✨Tip Number 3
Prepare for those interviews! Brush up on your technical knowledge and be ready to discuss your thought process. We love candidates who can break down complex ideas into simple terms, so practice explaining your work clearly.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we’re always on the lookout for passionate individuals who want to shape something meaningful in the machine learning space.
We think you need these skills to ace Head of Machine Learning
Some tips for your application 🫡
Show Your Passion for Ownership: In your application, make sure to highlight your desire to take ownership of projects. We want to see that you’re excited about leading the evolution of a statistical model and shaping its future. Share examples of how you've taken charge in previous roles!
Keep It Simple: When explaining your technical skills, remember to keep it straightforward. We appreciate candidates who can break down complex ideas into simple terms. Use clear language to describe your experience with Python and ML frameworks like PyTorch.
Demonstrate Your Curiosity: We love candidates who are curious about decision-making processes! In your written application, share your thoughts on how you approach modelling reality versus just predicting outcomes. Show us your scientific mindset and willingness to question assumptions.
Apply Through Our Website: Don’t forget to apply through our website! It’s the best way for us to receive your application and ensure it gets the attention it deserves. We can’t wait to see what you bring to the table!
How to prepare for a job interview at LinuxRecruit
✨Understand the Core of the Role
Before your interview, dive deep into what it means to take ownership of a statistical model. Familiarise yourself with how the platform simulates decision-making and be ready to discuss how you can contribute to its evolution.
✨Showcase Your Technical Skills
Be prepared to demonstrate your proficiency in Python and ML frameworks like PyTorch. Bring examples of past projects where you've trained models on large datasets, and be ready to explain your approach to complex problems.
✨Communicate Clearly
Practice breaking down complex technical ideas into simple terms. The interviewers will want to see how well you can communicate your thoughts, especially when discussing intricate concepts related to statistical methods and modelling.
✨Exhibit Curiosity and Integrity
Express your curiosity about human decision-making and how it relates to modelling reality. Be honest about your knowledge gaps and show a willingness to learn. This demonstrates self-awareness and a scientific mindset that aligns with the role.
