Senior Data Scientist @ Bayer
(práce v Polsku)

Senior Data Scientist @ Bayer

Polsko

Required Qualifications:

• Bachelor’s degree in Computer Science, AI, or a related field.
• Proven experience in AI/ML development with a focus on infrastructure or system monitoring.
• Strong programming skills in Python, Java, or Go, and familiarity with observability tools (e.g., Prometheus, Grafana, ELK, OpenTelemetry).
• Experience with cloud-native environments (Kubernetes, Docker) and cloud platforms (AWS, GCP, Azure).
• Understanding of APM concepts, telemetry data, and performance tuning.
• Ability to work collaboratively in cross-functional teams and communicate technical concepts clearly.

Preferred Qualifications:

• Experience with time-series data, anomaly detection, and real-time analytics.
• Familiarity with CI/CD, GitOps, and infrastructure-as-code (e.g., Terraform).
• Knowledge of ethical AI and responsible monitoring practices.

At Bayer we’re visionaries, driven to solve the world’s toughest challenges and striving for a world where ,Health for all, Hunger for none’ is no longer a dream, but a real possibility. We’re doing it with energy, curiosity and sheer dedication, always learning from unique perspectives of those around us, expanding our thinking, growing our capabilities and redefining ‘impossible’. There are so many reasons to join us. If you’re hungry to build a varied and meaningful career in a community of brilliant and diverse minds to make a real difference, there’s only one choice.

,[Design and develop AI-driven systems with a focus on infrastructure observability and application performance monitoring (APM)., Build intelligent agents capable of monitoring, analyzing, and optimizing system performance in real-time., Leverage A2A and MCP protocols to enable autonomous coordination between monitoring agents., Integrate AI models into observability stacks (e.g., Prometheus, Grafana, OpenTelemetry) to enhance system insights., Collaborate with DevOps, SREs, and platform teams to define performance metrics and thresholds., Develop predictive models for anomaly detection, root cause analysis, and capacity planning., Ensure high availability and reliability of AI monitoring solutions in production environments., Participate in Agile development and contribute to continuous improvement of observability practices., Document system architectures, monitoring strategies, and AI model behaviors.] Requirements: AI/ML, Python, Java, Go, Kubernetes, Docker, Azure, AWS, CI/CD, AI Additionally: Sport subscription, Private healthcare, International projects, Canteen, In-house trainings.

Kategorie

data

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