Data Science Engineer AWS B2B

Responsibilities As a Data Science Engineer, you will develop data-driven solutions on AWS — combining data analysis, feature engineering, statistical thinking, and hands-on data engineering. You will work closely with business, engineering, and platform teams to turn data into actionable insights and scalable analytical workflows. Responsibilities: Explore, analyze, and interpret large datasets. Develop features, analytical logic, and data science workflows. Build and maintain data pipelines on AWS. Apply statistical methods and machine learning where useful. Support the operationalization of analytical solutions. Collaborate with engineering and platform teams. Document and present results to business and technical stakeholders. Qualifications Bachelor’s or master’s degree in Computer Science, Engineering, IT, or a related field. 3+ years of professional experience as a Data Scientist, Data Engineering, or a hybrid analytics role. Strong Python skills, e.g. pandas, NumPy, scikit-learn. Good SQL skills and experience working with data platforms. Solid understanding of statistics, data analysis, and feature engineering. Hands-on experience with AWS data services, e.g. S3, Glue, Athena, Lambda, SageMaker, Step Functions, Redshift, or EMR. Experience with ETL/ELT pipelines, orchestration, or data workflows. Fluent English and Polish. Willingness to visit the Katowice office once per month and travel to the client’s office in Lisbon. Nice to have Experience with ML model development or model evaluation. Git, CI/CD, Docker, or infrastructure-as-code. Customer-facing project experience. About Data Reply As part of the Reply group, Data Reply offers a wide range of services that support customers in becoming data driven. We operate in various industries and business areas and work intensively with our customers so that they can achieve meaningful results through the effective use of data. Data Reply offers many years of experience in transformation projects to achieve “data-driven companies”. We focus on the development of data platforms, machine learning solutions and streaming applications - automated, efficient, and scalable - without making any compromises in IT security.