Data Engineer/Data Scientist

Sineta, in collaboration with its partners, brings cutting-edge technologies and innovations to the Czech and European markets. We specialize in the design, development, and support of quality information systems for ŠKODA AUTO and its international plants. We are seeking a Mid-Level Data Engineer/Data Scientist with 2-3 years of professional experience to join our team, focusing on leveraging manufacturing data to drive operational excellence and innovation. The ideal candidate will be adept at both building and maintaining data infrastructure and applying advanced analytical techniques, including AI/ML, to solve real-world business problems.

• Data Pipeline Development: Design, build, and maintain robust and scalable data pipelines to ingest, transform, and load complex manufacturing data from various sources.
• Data Analysis & Modeling: Perform exploratory data analysis (EDA) and develop AI/Machine Learning models, particularly for predictive analytics (e.g., equipment failure, quality control, demand forecasting).
• Agentic AI Development: Design, build, and deploy agentic AI applications to automate complex decision-making processes within the manufacturing environment. This includes building LLM's for processing unstructured data like maintenance logs and allow for interaction with factory personnel i natural language.
• Data Visualization & Reporting: Create compelling dashboards and reports to visualize key performance indicators (KPIs), model results, and actionable insights for stakeholders using appropriate tools.
• Cloud Environment Utilization: Collaborate with development and operations teams to deploy and manage data science workflows in cloud environments.

• 2-3 years of experience in a Data Engineering or Data Science role.
• Strong proficiency in Python and its relevant libraries for data manipulation (e.g., Pandas, NumPy), machine learning (e.g., Scikit-learn, TensorFlow, PyTorch), and data visualization (e.g., Matplotlib, Seaborn).
• Solid understanding of relational and NoSQL databases, SQL proficiency, and experience working with large datasets.
• Proven ability to analyze complex data sets and translate business problems into analytical solutions.

Preferred (Nice-to-Have) Experience

• Cloud Computing: Hands-on experience with at least one major cloud platform and its associated Machine Learning services, such as:
• o Amazon Web Services (AWS), especially SageMaker and Badrock
• o Microsoft Fabric or Azure ML
• o Google Cloud (GCP), especially Vertex AI.
• Advanced Analytics: Experience with time-series analysis, statistical process control, and advanced machine learning techniques relevant to industrial data
• Software Engineering Principles: Familiarity with version control (Git) and MLOps practices for deploying and monitoring models in production.

• A team of professionals who share the same mindset as you. They want to work independently while still having the support of a larger team. They know how to support each other.
• After onboarding, home office up to 5 days a week (as agreed).
• 4 weeks of vacation, 1 week of Sineta days, and 2 days of personal leave.
• Contribution to pension insurance, electronic meal vouchers.
• High-quality technical equipment, company mobile plan.