Data Scientist

Albatross AI; France; Remote; EUR 65,000 - 100,000; Full time

Benefits offered by this job

Flexibility to work from anywhere in E

Learning and conference budget

Job summary

Albatross is seeking a Data Scientist to design and deploy ML models powering real-time personalization for our customers. You will own ML workstreams end-to-end, collaborating with Applied Scientists and Engineers to translate product needs into scalable ML solutions.

You will build models for ranking, recommendation, and personalization, engineer features, train and deploy in production, and iterate based on live feedback. Remote across Europe.

Qualifications

• Bachelor's degree in ML or STEM.
• Strong background in ML, statistics, or data science.
• Proficient in Python.
• Experience training and deploying ML models in production.
• Familiar with PyTorch, TensorFlow, or JAX.
• Experience with large-scale datasets and feature engineering.
• Strong communication skills in English.

Responsibilities

• Design and implement ML 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.

Skills

ML

Statistics

Data science

Python

Production ML

ML frameworks

Large-scale data

Independent work

English communication

Education

Bachelor's degree in Machine Learning or STEM

Tools

PyTorch

TensorFlow

JAX

AWS

GCP

Azure

Job 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

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