Project Manager

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Clinisys

WebsiteLinkedInAll Job Openings

1001 - 5000 employees

Founded 1988

☁️ SaaS

🤝 B2B

🔬 Science

SaaS • B2B • Science

Clinisys is a global provider of laboratory informatics and diagnostics software, offering laboratory information management systems (LIS/LIMS), cloud-based laboratory platforms, and related professional services to laboratories across healthcare, life sciences, environmental, food & beverage, and other sectors. With over 40 years of experience and more than 3,000 customers in 34 countries, Clinisys delivers solutions that support sample traceability, regulatory compliance, population-scale testing, and integration of emerging technologies such as AI. The company combines local market knowledge and global scale, backed by product development, support, and deployment teams to help organisations run efficient, compliant laboratory operations.

📋 Description

• Leverage AI-enabled project management and analytics tools to support planning, forecasting, and decision-making • Use predictive analytics, trend analysis, and scenario modelling to anticipate risks, delays, and resource constraints • Oversee projects involving AI-enabled, data-driven, or digital healthcare solutions, ensuring alignment with scope, regulatory requirements, and customer expectations • Drive adoption of automation, intelligent reporting, and AI-assisted monitoring tools to improve project execution • Monitor project performance using data dashboards, KPIs, and AI-driven performance insights

🎯 Requirements

• Bachelor’s degree in Project Management, Business Administration, or related field • PMP or equivalent certification • 3–5 years of experience in project management within services or healthcare environments • Experience with digital, data-driven, or software implementation projects • Exposure to AI-enabled or analytics-driven projects is a strong asset • Strong project management capabilities (planning, execution, risk management) • Proficiency with project management tools (e.g., Microsoft Project, Asana, Trello) • Solid understanding of AI/ML concepts, including supervised/unsupervised learning, predictive modelling, and intelligent automation • Familiarity with data visualization tools (e.g., Power BI, Tableau or similar) • Understanding of AI governance frameworks, including transparency, auditability, and risk management