Lead Data Scientist

Johnson Controls; Neuhausen am Rheinfall; Vor Ort; CHF 260.000 - 420.000; Vollzeit

Zusammenfassung

Johnson Controls is seeking a seasoned Leader of AI & Data Science to own the end-to-end AI strategy across four operations—GenAI & Agentic Platform, AI Operations, Statistical & ML Modeling, and Data Center AI for HVAC.

You will drive a multi-year roadmap, govern responsible AI, shepherd model risk management, oversee vendor relationships, and ensure AI initiatives deliver measurable business value at scale.

Qualifikationen

• Bachelor's or Master's in CS, Data Science, Engineering, Statistics, or related field (PhD a plus).
• 12+ years of data science/ML experience, including 5+ years in senior leadership managing multiple teams.
• Proven track record delivering production-grade AI/ML systems at enterprise scale.
• Hands-on familiarity with GenAI stack: LLMs, RAG, vector databases, agent frameworks, and evaluation tooling.
• Strong grounding in MLOps/AIOps and cloud platforms (AWS/Azure/GCP), containers, and CI/CD for ML.
• Ability to partner with business stakeholders and communicate impact to executives.
• Experience managing budgets, vendors, and cross-functional programs.

Aufgaben

• Define and execute multi-year AI/ML roadmap across four operations.
• Advise executive leadership on emerging AI technologies and business applications.
• Establish governance for responsible AI, model risk, data privacy, and regulatory compliance.
• Manage vendor relationships and build-vs-buy decisions.
• Lead design and scaling of enterprise GenAI platform and copilots.
• Own the operational backbone for AI/ML workloads: CI/CD, monitoring, drift detection, retraining.
• Develop data-center AI initiatives: thermal management, energy efficiency, predictive maintenance.

Kenntnisse

Strategic leadership

Executive communication

Stakeholder management

Budget and vendor management

People leadership

Problem solving

Ausbildung

Bachelor's or Master's degree in CS/Data Science/Engineering/Statistics (PhD a plus)

Jobbeschreibung

About The Role

We are seeking a seasoned Leader of AI & Data Science to lead our enterprise AI portfolio spanning four specialized operations: Generative AI & Agentic Platforms, AI Operations, Statistical & ML Modeling, and Data Center AI for our HVAC business. This leader will own the end-to-end AI strategy — from experimentation to production — ensuring AI initiatives deliver measurable business value, operate reliably at scale, and align with the company’s broader digital transformation goals.

Key Responsibilities

Strategic Leadership

• Define and execute the multi-year AI/ML roadmap across all four operations, aligned with business priorities and P&L impact.
• Act as the senior AI voice for the organization — advising executive leadership on emerging technologies (LLMs, agentic AI, edge AI) and their business applications.
• Establish governance frameworks covering responsible AI, model risk management, data privacy, and regulatory compliance.
• Manage vendor relationships (cloud providers, LLM providers, tooling), and build-vs-buy decisions.

GenAI & Agentic Platform

• Lead the design and scaling of an enterprise agentic AI platform (LLM orchestration, RAG pipelines, multi-agent workflows, tool/function calling, guardrails, and evaluation frameworks).
• Drive adoption of GenAI copilots and autonomous agents across internal and customer-facing use cases.
• Stay ahead of the rapidly evolving GenAI ecosystem (foundation models, fine-tuning, prompt engineering, agent frameworks) and set platform standards.

AI Operations

• Own the operational backbone for all AI/ML workloads: CI/CD for models, model monitoring, drift detection, retraining pipelines, observability, and incident response.
• Establish SLAs/SLOs for production models and GenAI services; drive reliability, latency, and cost optimization (including LLM inference cost management).
• Standardize the ML platform stack (feature stores, model registries, experiment tracking, deployment patterns) across the organization.

Statistical & ML Models for Business

• Oversee development of statistical, forecasting, and machine learning models supporting core business functions (e.g., demand forecasting, pricing, churn, service optimization, predictive maintenance).
• Ensure rigor in model development — experimental design, validation, explainability, and measurable business KPIs.
• Partner with business unit leaders to prioritize a portfolio of high-ROI analytics use cases.

Data Center AI for HVAC Business

• Lead AI/ML initiatives focused on data center development and operations — thermal management, cooling optimization, energy efficiency, capacity planning, and predictive insights for HVAC systems.
• Work closely with HVAC product, engineering, and field teams to translate sensor/telemetry data (BMS, IoT, chillers, CRAH/CRAC units) into actionable intelligence and product features.
• Develop digital twin, anomaly detection, and optimization models that improve PUE, uptime, and equipment lifecycle for data center customers.

People & Organizational Leadership

• Hire, mentor, and grow POD leads and a multidisciplinary team of data scientists, ML engineers, GenAI engineers, and MLOps engineers.
• Foster a culture of experimentation, engineering excellence, and business accountability.
• Define career paths, performance standards, and knowledge-sharing practices across PODs.

Required Qualifications

• Bachelor's or Master's degree in Computer Science, Data Science, Engineering, Statistics, or a related field (PhD a plus).
• 12+ years of experience in data science / machine learning, with 5+ years in senior leadership managing multiple teams or PODs.
• Proven track record of delivering production-grade AI/ML systems at enterprise scale.
• Hands-on familiarity with the modern GenAI stack: LLMs (OpenAI, Anthropic, open-source), RAG, vector databases, agent frameworks (e.g., LangGraph, CrewAI, AutoGen), and evaluation/guardrail tooling.
• Strong grounding in MLOps/AIOps practices and cloud platforms (AWS / Azure / GCP), containerization, and CI/CD for ML.
• Solid foundation in classical statistics and ML (regression, time series, classification, optimization) and their application to business problems.
• Demonstrated ability to partner with business stakeholders, translate ambiguous problems into AI solutions, and communicate impact to executives.
• Experience managing budgets, vendors, and cross-functional programs.

Preferred Qualifications

• Domain experience in HVAC, data centers, energy management, building automation, or industrial IoT.
• Familiarity with time-series/telemetry data at scale, digital twins, physics-informed ML, or reinforcement learning for control/optimization (e.g., cooling optimization).
• Experience with edge AI deployment and BMS/SCADA integration.
• Knowledge of responsible AI frameworks, model governance, and relevant regulations.
• Publications, patents, or recognized contributions in AI/ML.

Key Competencies

• Strategic thinking with hands-on technical depth
• Multi-team leadership and talent development
• Executive communication and stakeholder management
• Bias for action and outcome-driven delivery
• Comfort with ambiguity in a fast-evolving AI landscape