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- Tasks: Design and deploy machine learning models for real-time personalisation.
- Company: Innovative AI company transforming user experience with cutting-edge technology.
- Benefits: Work remotely across Europe with a budget for learning and attending events.
- Why this job: Join a dynamic team and make an impact in the AI space.
- Qualifications: Bachelor's in Machine Learning or STEM, strong ML background, and Python skills.
- Other info: Collaborate with experts and enjoy flexibility in your work environment.
The predicted salary is between 50000 - 70000 £ per year.
At Albatross, we’re building the second pillar of AI: a perception layer that understands how users actually experience content, in real time. Trained on live user interactions, Albatross learns and reasons on the fly. Our technology powers real‑time, in‑session discovery by adapting to evolving user interests. We have raised significant funding and our platform already operates at scale, with billions of events being processed and hundreds of millions of predictions served.
Location: Remote in Europe.
The Role: As a Data Scientist, you will design and deploy machine learning models that power real‑time personalization for our customers. You will own defined workstreams of ML projects end‑to‑end, and you will work closely with applied scientists and engineers to translate product and customer needs into scalable ML solutions. More specifically, you will:
- Design and implement machine learning models for ranking, recommendation, and personalization.
- Define feature engineering pipelines and modeling strategies for customer use cases.
- Train, evaluate, and deploy models using our internal ML tooling and infrastructure.
- Own project workstreams from data preparation through production deployment.
- Collaborate with Applied Scientists to integrate new algorithms into production systems.
- Contribute improvements to internal ML tooling and experimentation infrastructure.
- Monitor model performance and iterate based on real-world feedback.
Requirements:
- Bachelor's degree in Machine Learning or STEM.
- Strong background in machine learning, statistics, or data science.
- Solid programming skills in Python.
- Experience training and deploying ML models in production environments.
- Familiarity with ML frameworks such as PyTorch, TensorFlow, or JAX.
- Experience working with large-scale datasets and feature engineering pipelines.
- Ability to work independently on moderately complex ML problems.
- Strong communication skills in English.
Nice to Have:
- Experience with recommender systems, ranking models, or search.
- Experience with large-scale experimentation and evaluation pipelines.
- Familiarity with learning-to-rank models, bandits, or reinforcement learning.
- Experience working with cloud environments such as AWS, GCP, or Azure.
Benefits:
- Flexibility to work from anywhere across Europe.
- Budget for learning and training, attend events and conferences.
Data Scientist employer: Albatross
Contact Detail:
Albatross Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist
✨Tip Number 1
Network like a pro! Reach out to people in the industry, especially those at Albatross. A friendly chat can open doors and give you insights that a job description just can't.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your machine learning projects. Whether it's a GitHub repo or a personal website, let your work speak for itself.
✨Tip Number 3
Prepare for the interview by brushing up on your ML knowledge. Be ready to discuss your experience with Python and frameworks like PyTorch or TensorFlow. We want to see your passion for data science!
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows you're genuinely interested in joining the Albatross team.
We think you need these skills to ace Data Scientist
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Data Scientist role. Highlight your experience with machine learning, Python, and any relevant projects you've worked on. We want to see how your skills align with what we're looking for!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about AI and how your background makes you a great fit for Albatross. Keep it engaging and personal – we love to see your personality come through.
Showcase Your Projects: If you've worked on any cool ML projects, make sure to mention them! Whether it's a personal project or something from your previous job, we want to see how you've applied your skills in real-world scenarios. Include links if possible!
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way to ensure your application gets into the right hands. Plus, it shows us that you're genuinely interested in joining our team at Albatross!
How to prepare for a job interview at Albatross
✨Know Your ML Models
Make sure you brush up on the machine learning models you've worked with. Be ready to discuss how you've designed, trained, and deployed them in production. Albatross is looking for someone who can hit the ground running, so showcasing your hands-on experience will definitely impress.
✨Feature Engineering is Key
Prepare to talk about your approach to feature engineering. Albatross values candidates who can define effective pipelines for customer use cases. Think of specific examples where your feature engineering made a significant impact on model performance.
✨Showcase Your Collaboration Skills
Since you'll be working closely with applied scientists and engineers, it's crucial to demonstrate your ability to collaborate. Share experiences where you successfully integrated new algorithms or worked on cross-functional teams to solve complex problems.
✨Be Ready for Real-World Scenarios
Albatross wants to know how you monitor model performance and iterate based on feedback. Prepare to discuss any real-world challenges you've faced and how you adapted your models accordingly. This shows that you can think critically and respond to evolving user needs.