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Lead Data Scientist

Job in 8212, Neuhausen am Rheinfall, Kanton Schaffhausen, Switzerland
Listing for: Johnson Controls Fire Suppression IP GmbH
Full Time position
Listed on 2026-08-29
Job specializations:
  • IT/Tech
    AI Engineer (Applied/Software), Machine Learning/ ML Engineer, AI Business & Operations, Data Scientist
Salary/Wage Range or Industry Benchmark: 180000 - 240000 CHF Yearly CHF 180000.00 240000.00 YEAR
Job Description & How to Apply Below

Lead Data Scientist

Johnson Controls Fire Suppression IP GmbH Vacant since : 13.08.2026 Number of jobs : 1 8212 Neuhausen am Rheinfall (SH) 100% Immediately Permanent

Position Summary

We are looking for an experienced Lead Data Scientist to drive the organization's enterprise-wide Artificial Intelligence and Data Science strategy. This leadership role is responsible for advancing AI capabilities across Generative AI, Machine Learning, MLOps, and Data Center AI applications within the HVAC business.

As the senior AI leader, you will oversee the full lifecycle of AI initiatives, from ideation and experimentation through production deployment and business adoption. You will lead multidisciplinary teams of Data Scientists, ML Engineers, GenAI Specialists, and MLOps Engineers while ensuring AI solutions deliver measurable business outcomes, operational excellence, and competitive advantage.

Key Responsibilities

  • AI Strategy & Leadership
  • Define and execute the company's long-term AI and Data Science strategy.
  • Align AI initiatives with business objectives,
  • digital transformation priorities, and financial targets.
  • Advise executive leadership on emerging AI technologies and their business applications.
  • Establish governance frameworks covering responsible AI, data privacy, risk management, and regulatory compliance.
  • Manage strategic partnerships with AI vendors, cloud providers, and technology partners.

Generative AI & Agentic AI Platforms

  • Lead the development and scaling of enterprise Generative AI platforms and intelligent agent solutions.
  • Drive the adoption of AI copilots and autonomous agents across internal and customer-facing business processes.
  • Define standards for LLMs, Retrieval-Augmented Generation (RAG), multi-agent workflows, prompt engineering, evaluation frameworks, and AI governance.
  • Continuously evaluate emerging AI technologies and identify opportunities for innovation and business value creation.

AI Operations & MLOps

  • Oversee the operational framework for AI and machine learning solutions at scale.
  • Implement best practices for model deployment, monitoring, retraining, performance management, and incident response.
  • Ensure reliability, scalability, security, and cost efficiency of AI services.
  • Standardize machine learning platforms, model registries, experiment tracking, feature management, and deployment processes.

Machine Learning & Advanced Analytics

  • Lead the development of predictive, statistical, and machine learning models supporting key business functions.
  • Drive initiatives such as demand forecasting, pricing optimization, customer analytics, predictive maintenance, and operational efficiency improvements.
  • Ensure robust model development practices, including validation, explainability, and performance measurement.
  • Collaborate with business stakeholders to identify and prioritize high-impact AI use cases.

Data Center AI & HVAC Applications

  • Lead AI initiatives focused on data center operations and HVAC optimization.
  • Develop models supporting thermal management, cooling optimization, energy efficiency, capacity planning, and predictive maintenance.
  • Collaborate with product, engineering, and field teams to transform IoT and telemetry data into actionable insights.
  • Drive innovation in areas such as digital twins, anomaly detection, optimization algorithms, and intelligent operational solutions.
  • Team Leadership & Talent Development
  • Build, lead, and develop high-performing teams of Data Scientists, AI Engineers, and MLOps specialists.
  • Create a culture of innovation, collaboration, continuous learning, and accountability.
  • Mentor technical leaders and support career development across the organization.
  • Define performance standards, career pathways, and knowledge-sharing practices.

Required Qualifications

  • Bachelor's or Master's degree in Computer Science, Data Science, Statistics, Engineering, Mathematics, or a related field.
  • PhD is considered an advantage.
  • Minimum 12 years of experience in Data Science, Artificial Intelligence, or Machine Learning.
  • At least 5 years of leadership experience managing multiple teams or technical functions.
  • Proven track record of delivering enterprise-scale AI and machine learning solutions.
  • Strong…
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