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Introduction & Summary:
We are seeking an experienced professional for the role of Machine Learning Engineer / Data Scientist to join a team focused on data analysis and machine learning projects. This hands-on role concentrates on designing, building, implementing, and maintaining production-level ML solutions and data processing.
Main Responsibilities:
Design and implementation of Machine Learning and Data Science solutions.
Building and enhancing data processing workflows using Apache Spark.
Preparing ML models and deploying them to production environments.
Maintaining and evolving existing production solutions.
Performance analysis and identifying bottlenecks.
Optimizing processes for performance and cost efficiency.
Working with large data sets and crafting SQL queries.
Creating and integrating solutions through REST API.
Working with containers and basic DevOps tasks.
Collaborating with technical teams and participating in developing end-to-end solutions.
Key Requirements:
Minimum of 5 years of commercial experience in Machine Learning / Data Science / ML Engineering.
Practical experience in deploying and maintaining ML solutions in production.
Very good proficiency in Python, especially with libraries such as:
pandas,
scipy,
matplotlib.
Hands-on experience with Apache Spark.
Strong experience in classic Machine Learning.
Good knowledge of SQL and ability to write queries independently.
Experience with Azure Synapse.
Familiarity with basic DevOps tasks:
Docker,
Kubernetes,
setting up and managing containers independently,
performing basic administrative tasks.
Understanding of REST API.
Good understanding of machine learning concepts.
Nice to Have:
Snowflake – not required.
Hadoop.
Linux environment administration.
NumPy.
Experience in areas such as:
process mining,
churn analysis,
fraud prevention,
NLP.
Experience with Generative AI / LLM solutions.
Infrastructure and cloud experience.
Very good knowledge of Scala or Java
Other Details:
Industry: banking
Collaboration model: hybrid in Warsaw - once every 2 weeks in the office
Project language: English
Project duration: 12 months + possible extensions
Starting collaboration: ASAP
Contract type: B2B