Software Engineer Data Science

Become part of our team at the "Software Engineering & IT" business center in Aarau. We develop sophisticated software, machine learning, and AI solutions for highly specialized applications, creating direct added value for our customers from their data.

Lead our projects to success: From exploratory data analysis and feasibility assessment to model development, application development, and implementation.

Your main tasks and responsibilities

• Data Engineering & Data Pipelines: Connecting and integrating diverse data sources (e.g., SQL/NoSQL, APIs, files, IoT). Developing robust data pipelines for data extraction, cleansing, transformation, and validation. Implementing feature engineering and ensuring high data quality and traceability.
• Machine Learning & Modeling: Design, training, evaluation, and optimization of machine learning models using various approaches (e.g., XGBoost, Deep Learning, Reinforcement Learning). Development of models for different data types: structured and unstructured, from multidimensional time series to images.
• Reproducible and traceable ML training: Development of traceable training and experimentation environments (experiment tracking, versioning of data and models, model registry). Ensuring transparency, reproducibility, and governance throughout the entire ML lifecycle.
• Use of AI in solutions and development process: Collaboration in the conception, design, prototyping and implementation of modern solutions with integrated AI components (LLMs, RAG, tool integration), as well as broad use of modern AI tools in the development process.
• Architecture and development of data-driven software solutions: Conception, design, prototyping, and implementation of modern software applications with integrated ML and AI components and user-centric interfaces. Integration of models into production systems (APIs, microservices, edge/cloud).
• MLOps, DataOps & DevOps: Use of modern tools and methods for automating data and ML workflows. Setting up CI/CD pipelines for ML systems, monitoring models in operation (performance, drift), and structured quality assurance.
• Collaboration & Enablement: Close collaboration with software developers, architects, and subject matter experts at our clients. Further development of internal standards, best practices, and our data and AI tooling.

Your profile and expertise:

• Education: Very good degree (FH, ETH, Uni) in computer science, data science, mathematics, physics or a comparable field.
• Data Engineering: Solid experience in handling data sources (SQL, NoSQL, unstructured data), building data pipelines, and feature engineering. Understanding of data modeling, data quality, and performance optimization. Experience with visualization and BI tools is a plus.
• Machine Learning: Several years of experience in the design, training, and deployment of ML models (e.g., CNN, YOLO, XGBoost). Familiarity with common frameworks (e.g., scikit-learn, PyTorch, TensorFlow) as well as evaluation methods, hyperparameter tuning, and model validation. Experience with time series analysis or reinforcement learning is a plus.
• Software Engineering: Excellent programming skills (especially Python), as well as experience with modern software architectures, API design, testing, code reviews, and collaborative development. Significant experience using AI tools in the development process (e.g., GitHub Copilot, Claude Code). Knowledge of UI or web technologies, C#, or Java is advantageous.
• MLOps & Operations: Experience with experiment tracking, model versioning and deployment strategies (e.g. MLflow).
• DevOps & Quality Assurance: Initial experience with CI/CD, automated testing, monitoring, and observability. Structured approach to the performance, stability, and scalability requirements of production systems.
• Personal skills: Strong analytical skills, high quality standards, and a passion for data-driven solutions, close collaboration with clients, and interdisciplinary projects. A structured work approach, sound technical judgment, and enthusiasm for innovative solutions in demanding industrial environments.
• Languages: Very good German and English skills, both spoken and written.

Why Helbling?

They accompany your projects from initial data analysis and modeling to productive integration and operation. They work on technologically demanding projects with a high level of technical expertise, ranging from intelligent analysis platforms and predictive and optimization models to strategic data and AI initiatives in a wide variety of industries.

We offer you creative freedom, modern technologies and an environment that combines technological excellence with entrepreneurial thinking – interdisciplinary, practical and with real impact on the customer.