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 a dynamic team on a 12-month contract. The role is fully remote, offering the chance to work on real-world data and advanced ML techniques.

You will apply embeddings, semantic similarity, LLMs, and both supervised and unsupervised models, and you will collaborate with engineering and product teams to explain model behavior and impact.

Qualifications

• Strong foundation in ML with hands-on modeling on real data.
• Proficient in Python and SQL for data wrangling and modeling.
• Experience with embeddings, semantic similarity or LLMs.
• Hands-on experience training supervised and unsupervised models, including NLP tasks.
• Familiarity with neural networks and transformer architectures.
• Proficiency with ML frameworks such as TensorFlow, PyTorch, PyCaret.
• Experience retraining a taxonomy classifier or maintaining models in production.
• Ability to define baselines, metrics, and error analysis to show quality improvements.
• Ability to explain model behavior, tradeoffs, and edge cases to engineers and business partners.

Skills

Strong applied ML fundamentals

Python

SQL

Embeddings / semantic similarity / LLM

Training supervised/unsupervised

Neural networks / transformers

Experimental judgment

Explain model behavior to stakeholders

Tools

TensorFlow

PyTorch

PyCaret

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.