Data Scientist at Albatross

, , Germany -

Full Time

Start Date

Immediate

Expiry Date

15 Jun, 26

Salary

0.0

Posted On

17 Mar, 26

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Machine Learning, Statistics, Python, Model Deployment, PyTorch, TensorFlow, JAX, Feature Engineering, Recommender Systems, Ranking Models, Bandits, Reinforcement Learning, AWS, GCP, Azure

Industry

Description

Location Remote in Europe. Albatross 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, in real-time. 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. 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. 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. Flexibility to work from anywhere across Europe. Budget for learning and training, attend events and conferences.

Responsibilities

The Data Scientist will be responsible for designing and deploying machine learning models focused on real-time personalization, ranking, and recommendation for customers. This involves owning ML projects end-to-end, from data preparation and feature engineering through production deployment and performance monitoring.