Data Scientist / Machine Learning Engineer

Wynagrodzenie

B2B: 15000 – 22000 PLN / mies. netto
umowa o pracę: 12000 – 17000 PLN / mies. brutto

At cloudatus, we help customers drive technical solution design, development, deployment and support them alongside their cloud journey. As an all‑cloud service and consulting provider for midsize and large enterprises, we speak cloud fluently: IaaS, PaaS, SaaS – you name it.

We are looking for a Data Scientist / Machine Learning Engineer to join our engineering team and deliver ML solutions for international enterprise projects.

Your Role

As a Data Scientist / Machine Learning Engineer you will design, build and deploy machine learning and data science solutions in an enterprise environment. You will work closely with cross‑functional teams to turn complex data into actionable insights and integrate models into existing business processes and IT infrastructures.

Your Responsibilities

• Design, develop and implement machine learning and data science solutions in an enterprise environment.

• Preparation and analysis of complex datasets from various sources, including handling missing and incorrect values

• Application and optimisation of machine learning methods (e.g. linear regression, random forest, K‑nearest neighbors, neural networks, gradient boosting, clustering methods, reinforcement learning, decision/regression trees), including feature engineering and hyperparameter tuning

• Building models using Python and/or R and standard data‑science libraries

• Using cloud platforms (e.g. Azure ML, AWS SageMaker) and contributing to automated ML pipelines and MLOps practices

• Collaboration with cross‑functional teams to integrate ML solutions into business processes and IT systems

Your Profile

• Solid experience in the design, development and implementation of ML and data science solutions in an enterprise environment

• In‑depth knowledge of statistics and data analysis (e.g. confidence intervals, significance tests, survival analyses, etc.)

• Strong programming skills in Python (R is a plus)

• Experience with cloud platforms such as AWS SageMaker or Azure ML; knowledge of ML pipelines and MLOps is desirable

• approach to work, with strong