Senior Data Scientist

Auxo Talent; Polska; Remote; PLN 180,000 - 280,000; Full time

Job summary

Auxo Talent is seeking a Senior Data Scientist to join their dynamic team on a 12-month contract. The role is remote, enabling collaboration across time zones and stakeholders.

You will apply advanced ML to real datasets, build and evaluate models, and work with embeddings, LLMs, NLP tasks, and neural networks. Strong Python/SQL, production-minded mindset, and ability to explain model behavior to engineers and business partners are essential.

Qualifications

• Strong applied ML fundamentals with hands-on modelling on real data.
• Excellent Python and SQL skills.
• Experience with embeddings, semantic similarity, LLMs.
• Hands-on training of supervised and unsupervised models including NLP.
• Knowledge of neural networks and transformer architectures.
• Proficiency with ML frameworks such as TensorFlow, PyTorch, PyCaret.
• Experience retraining taxonomy classifiers or production models.
• Experimental judgment with baselines, metrics and error analysis.
• Ability to explain model behavior to engineers and business partners.

Skills

Applied ML

Python

SQL

Embeddings/LLMs

Supervised/Unsupervised

Neural Networks

TensorFlow

PyTorch

PyCaret

Taxonomy classifiers

Job description

Our client currently seeks a Senior Data Scientist to join their dynamic team on a 12 month contract. This role is remote.

Required Skills

• Strong applied ML fundamentals, with hands-on experience building and evaluating models on real data.
• Excellent Python and SQL skills.
• Practical experience with embeddings, semantic similarity, LLMs, or related AI techniques.
• Hands-on experience training supervised and unsupervised models, including classification and NLP tasks.
• Working knowledge of neural network and transformer architectures.
• Proficiency with common ML frameworks such as TensorFlow, PyTorch, and PyCaret.
• Experience retraining a taxonomy classifier or maintaining classification models in production.
• Experimental judgment: able to define baselines, metrics, test sets, and error analysis that show whether quality improved.
• Ability to explain model behavior, tradeoffs, and edge cases clearly to engineering and business partners.