Jobs at Dotmatics

As a Senior Application Scientist, you will implement Dotmatics solutions in labs, ensuring project success through collaboration, training, and integration with existing systems.

Lead and operationalize a company-wide AI governance program: build frameworks, assess AI risks and use cases, embed controls in SDLC, run governance council, liaise with Siemens consortium, handle regulatory compliance (EU AI Act, NIST AI RMF), produce reporting, and deliver training and documentation across Product, Engineering, Legal, Privacy, HR and Security.

Develop and maintain automated test suites for a scientific software platform using Cypress, TypeScript, Cucumber, and Playwright. Own quality for an application module, design functional, regression, and integration tests, investigate defects, document bugs in JIRA, verify fixes, and maintain reliable CI test pipelines. Collaborate with developers, scientists, and DevOps engineers while performing manual exploratory testing and expanding API-level coverage.

Provide global People & Organization (P&O) support including policy implementation, employee relations case management, manager advisory, immigration/visa support, onboarding/offboarding, Workday administration, Jira/mailbox triage, reporting, and project support to HRBPs and managers.

Senior Business Analyst for Dotmatics Luma team translating product strategy into detailed user stories, acceptance criteria, and backlog items within Agile/Scrum. Collaborates with Product, Engineering, QA, UX, and scientists; performs requirements elicitation, process analysis, UAT, and supports product discovery, analytics-driven improvements, and cross-team delivery for a multi-tenant scientific SaaS platform.

Lead EMEA sales strategy and a regional team to sell cross-portfolio scientific and manufacturing SaaS solutions (ELN, LIMS, MES, PLM, analytics, AI). Drive territory and named-account coverage, pipeline generation, complex multinational negotiations, partner/channel engagement, and cross-functional collaboration to win and expand large enterprise deals.

Design, build, and maintain scalable analytics models and automated reporting. Partner with Sales, Product, Marketing, and Finance to define KPIs, deliver ad hoc analysis, improve data quality and observability, and establish analytics engineering best practices to enable self-service analytics.

Own cloud architecture intelligence and cost optimization: analyze cloud spend, identify inefficiencies, build dashboards, enforce governance, partner with engineering/finance to drive cost-conscious design and operations.