Top Tech Jobs & Startup Jobs

Owns global payroll delivery, statutory compliance, controls, vendor management, and service standards across all regions. Leads global payroll and time-tracking consolidation, including operating-model design, technology selection, country deployments, governance, and change management. Establishes AI and automation strategies to improve accuracy, reduce manual work, and strengthen preventive controls. Manages distributed payroll leadership teams and partners with Finance, Tax, Legal, Treasury, HR Technology, auditors, and regulators.

Develop scalable backend services, enterprise APIs, microservices, integration platforms, and cloud-native applications connecting enterprise systems, manufacturing operations, AI platforms, and cloud services. Responsibilities include API-first and event-driven integration, containerized deployments, CI/CD, security, observability, reliability, and performance optimization. The role collaborates with software, data, AI, and smart factory engineering teams to deliver reusable platform capabilities for intelligent manufacturing.

Designs and evolves enterprise data architecture supporting global manufacturing, supply chain, procurement, logistics, quality, and engineering operations. Defines data models, integration patterns, governance standards, metadata, lineage, and reusable data products across enterprise systems and cloud platforms. Partners with engineers, architects, AI specialists, governance teams, and business leaders to enable analytics, AI, digital twins, reporting, and smart manufacturing initiatives.

Develop machine learning, statistical, optimization, computer vision, Generative AI, and Agentic AI solutions for smart manufacturing. Analyze operational data, build production-ready AI applications, support cloud deployment and model monitoring, and collaborate with manufacturing, engineering, supply chain, quality, IT, and software teams to improve quality, productivity, reliability, and decision-making.

Develop statistical and machine-learning models for product demand forecasting across geographies. Analyze forecast accuracy, bias, and planning deviations; conduct experiments and root-cause analysis; and communicate insights to demand planners and business stakeholders. Productionize analytical models, recommend data strategies, identify data science opportunities, and educate teams on advanced forecasting approaches. The role supports integrated business planning, inventory decisions, and supply planning.

Leads talent acquisition strategy and execution across the Americas, managing recruiting teams, workforce planning, senior stakeholder partnerships, hiring operations, metrics, technology, vendors, employer branding, and pipelines for scientific, engineering, commercial, manufacturing, and corporate talent. The role requires scaling high-volume and specialized hiring across multiple markets while improving recruiting processes, candidate experience, analytics, and organizational effectiveness.

Own data governance and quality for critical commercial data assets. Define metadata, ownership, stewardship, lineage, quality standards, and monitoring processes; manage catalog and glossary content; profile data and lead remediation; support Microsoft Fabric, Power BI, Snowflake, and enterprise analytics initiatives; and partner with business, architecture, engineering, and analytics stakeholders to deliver trusted, discoverable, AI-ready data.

Sell analytical instrumentation, software, accessories, and services through inbound and outbound channels. Manage customer relationships, sales pipelines, forecasts, CRM updates, and territory opportunities across chromatography and spectroscopy products. Identify and develop new business, retain existing customers, address customer needs, and collaborate with field staff and cross-functional teams. The role requires a science degree, analytical techniques experience, and excellent Danish and English communication skills.

Build and maintain scalable enterprise data platforms, pipelines, integrations, and reusable data products for global manufacturing operations. Implement data governance, quality monitoring, metadata, lineage, and master data practices. Develop cloud-native, batch, streaming, and event-driven solutions supporting analytics, AI, reporting, smart factories, and digital twins. Collaborate with architects, engineers, data scientists, and operations stakeholders while applying DevOps, observability, and CI/CD practices.

Develop secure, responsive operational applications for manufacturing and frontline workflows across mobile, tablet, and industrial devices. Integrate applications with SAP, MES, enterprise data platforms, AI services, and backend APIs. Build offline-capable workflows, digital instructions, inspections, maintenance tools, inventory transactions, and intelligent user experiences. Collaborate with cross-functional engineering and operations teams using Agile practices while evaluating emerging technologies such as wearables, barcode systems, voice interaction, and AI assistants.