Machine learning engineer in banking

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.

• 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.

• 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.
• Будет плюсом: 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

• 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