Working Student Data Science Chemical Engineering (mfd)

Job ID: 41814 Location: Munich Bavaria Germany Work Model: Hybrid

Navigance a young corporate start-up within Clariant is looking for a Working Student (m/f/d) for our Munich office. Youll join our data science team and help develop our cloud-based platform for industrial IoT data from chemical production plants. The work spans data integration and preparation statistical analysis and data-driven modelling.

Responsibilities:

• Build Python scripts to parse process and integrate customer data directly into our platform.
• Bring structure to heterogeneous real-world industrial datasets.
• Investigate process data using statistical methods and data-driven modelling.
• Connect data patterns with chemical and physical processes thats what makes the real difference.
• Work with data scientists process experts and the product team and bring your own ideas to the table.

Requirements:

• Bachelors degree completed Masters in progress at least one year remaining available 15h/week.
• Solid Python skills: you write read and debug code independently. AI tools are part of the job use them but understand judge and own the output.
• Hands-on experience with pandas NumPy scikit-learn TensorFlow or similar.
• Background in chemical or process engineering chemistry computer science or physics.
• Structured and proactive problem-solver comfortable with large real-world datasets.
• Clear communicator across technical and non-technical audiences.
• Fluent English; Chinese is a plus.

Our Offer:

• Real industrial data and real customer impact.
• Direct exposure to chemical production processes and advanced analytics.
• An interdisciplinary international team of engineers data scientists and software developers.
• Ownership of your work competitive pay and the perks of a modern company.

Your Contact:

Ann-Christin Kaiser

Talent Acquisition Partner EMEA

Navigance supports chemical production processes with advanced data analytics and the latest AI-based tools in an easy to use web-based interface so that our customers reach optimal performance of their plants and improve sustainability. We do this by guiding operators partnering with plant engineers and supporting production managers to reach their goals. We use a unique combination of data modeling know-how machine learning and catalytic process expertise to build and deliver customer-specific process models in a cloud-based platform. Our team consists of process engineers data scientists software developers and market experts.