Data Scientist

• Technical responsibility for developing, selecting, evaluating, and standardizing quality analytics methods, data models, KPI systems, and reusable analytical components.
• Independently analyze complex measurement, laboratory, process, and quality data, and derive robust areas for action and decision-making foundations.
• Develop, harmonize, and validate statistical metrics, quality indicators, and models for detecting trends, deviations, and anomalies.
• Apply and evaluate SPC, trend, correlation, outlier, and process capability analyses.
• Design and implement data models, automated data preparation and reporting processes, dashboards, reports, and self-service analytics solutions.
• Develop data analytics solutions using Python and SQL, and establish standards for data quality, KPI definitions, calculation logic, and documentation.
• Evaluate and validate predictive analytics and AI applications, and transition suitable solutions into practical use.
• Provide technical coordination for analytics projects from requirements analysis through implementation.
• Advise and empower the relevant departments, and transfer established methods, standards, and solutions to additional processes and sites.

Quality Data Scientist – m/f/d

• Teach engaging Data Science and Data Analytics topics
• Conduct hands-on workshops covering Python, SQL, Pandas, Tableau, Machine Learning and more
• Guide and support students through projects and assignments
• Collaborate with other instructors
• Contribute to improving teaching content
• Provide feedback, mentorship and motivation throughout students’ learning journeys
• Participate in student evaluations, final project mentoring and classroom events

Lead Instructor – Data Science

• Analyze and investigate existing detection logic built on multiple interconnected signals and rule-based expressions
• Understand and map complex data flows, processing pipelines, and dependencies across enterprise systems
• Identify redundancy, inefficiencies, and unnecessary complexity within current detection structures
• Propose simplification and optimization approaches while preserving detection quality and operational effectiveness
• Conduct exploratory analysis on large and complex datasets to validate hypotheses and support decision-making
• Assess downstream implications and operational risks of proposed changes before implementation
• Translate analytical findings into clear recommendations for technical and non-technical stakeholders
• Collaborate closely with engineers, data scientists, and security researchers to gather context and resolve blockers independently
• Operate effectively in a fast-paced environment with shifting priorities and short delivery cycles
• Contribute to improving analytical methodologies and approaches within the newly forming team

Senior Data Scientist

• Analyze and investigate existing detection logic built on multiple interconnected signals and rule-based expressions
• Understand and map complex data flows, processing pipelines, and dependencies across enterprise systems
• Identify redundancy, inefficiencies, and unnecessary complexity within current detection structures
• Propose simplification and optimization approaches while preserving detection quality and operational effectiveness
• Conduct exploratory analysis on large and complex datasets to validate hypotheses and support decision-making
• Assess downstream implications and operational risks of proposed changes before implementation
• Translate analytical findings into clear recommendations for technical and non-technical stakeholders
• Collaborate with engineers, data scientists, and security researchers to gather context and resolve blockers independently
• Operate effectively in a fast-paced environment with shifting priorities and short delivery cycles
• Contribute to improving analytical methodologies and approaches within the newly forming team