Lead – Advanced Analytics & AI

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Job Summary
The Group Data & Analytics Expert is responsible for leading advanced analytics initiatives developing data models and delivering insights that support strategic decision-making across the organization. This role ensures data quality governance and the effective use of analytics tools. This job profile is intended for recognized subject matter experts in a job area. Required to manage large projects or processes with limited oversight from manager. Coaches reviews and delegates work to lower level professionals.

Job purpose

Lead Sulzers Advanced Analytics & AI function and convert prioritized business problems into production-grade statistical machine-learning GenAI and agentic-AI solutions with measurable adoption and value. The role owns the Analytics & AI service portfolio delivery standards production lifecycle and specialist capability development within the enterprise Data Analytics & AI strategy set by the Global Head of Data Analytics & AI.

Main accountabilities and tasks

Own the Advanced Analytics & AI service portfolio: statistical learning machine learning optimization GenAI AI agents MLOps/LLMOps and AI FinOps aligned to enterprise priorities.

Translate approved business opportunities into a prioritized delivery portfolio with clear problem statements value hypotheses product/process owners adoption plans and production criteria.

Establish Analytics & AI engineering patterns jointly with Enterprise Data Architecture and Data Engineering including reusable AI services evaluation monitoring observability security and integration patterns.

Ensure solutions consume governed trusted data products and comply with enterprise data security privacy and responsible-AI requirements.

Lead the lifecycle from discovery and experimentation through industrialization deployment adoption monitoring and retirement; prevent proliferation of disconnected PoCs.

Lead coach and develop Data Scientists Forward Deployed AI Engineers & internal business / function teams; define skills ways of working and a scalable delivery model combining a high-calibre internal team with specialist augmented capacity.

Partner with business leaders and FDEs to redesign decisions and processes around analytics and AI with measurable user adoption and outcomes.

Own the augmented delivery and specialist partner model for Advanced Analytics & AI: plan capacity allocate work manage delivery quality cost and partner performance and ensure knowledge transfer into the internal team. Manage specialist vendors and platform partners and recommend make/buy/partner choices within enterprise architecture and investment guardrails.

KPIs: (1) Production adoption - priority analytics/AI solutions actively used in target decisions/processes; (2) Realized value - validated benefit from deployed portfolio; (3) Production effectiveness - agreed reliability/evaluation thresholds and time from approved use case to production.

ESH: comply with Sulzer ESH information-security data-protection and responsible-use requirements; ensure solutions do not compromise safe operational decision-making.

Job scope

Geography: Global

Key internal / external stakeholders:

Internal stakeholders: Global Head Data Analytics & AI; business/division leaders; Data Governance & Standards; Enterprise Data Architecture; Data Engineering & MDM; BI/Management Reporting; Enterprise Architecture; Cybersecurity; Legal/Privacy; process and product owners.

External stakeholders: Strategic technology providers specialist analytics/AI partners and systems integrators.

Decision authority: Functional delivery standards solution methods production readiness recommendations for advanced analytics and AI within approved enterprise and data architectures governance and budget.

Desired experience and qualifications

Work experience: 12 years in analytics data science AI or digital product engineering including 4 years leading multidisciplinary teams and production AI/analytics delivery.

Expertise (e.g. professional technical): Statistical learning (SL) machine learning (ML) optimization GenAI/LLMs and agentic AI patterns; MLOps / LLMOps; experimentation and evaluation; cloud/data platforms; APIs and enterprise integration; product/value management. Strong Snowflake/Azure familiarity desirable. Demonstrated application of analytics/AI to marketing sales manufacturing engineering supply chain commercial service or enterprise functions strongly preferred.

Education: Masters degree or equivalent in computer science engineering statistics mathematics operations research data science or related quantitative discipline; doctorate advantageous but not required.

Certifications: Snowflake / Microsoft / Salesforce platforms & ML/AI or data-platform certifications desirable.

Languages: Fluent professional English; additional languages advantageous.

Soft skills: Executive communication structured problem solving technical judgment talent development matrix influence value orientation and willingness to guide stakeholders from low-value experimentation to areas of high business impact.

Other: This is a senior hands-on functional lead. The ideal candidate must be technically proficient and capable of reviewing solution approaches experiments and production readiness.

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