Project Manager

QuantHealth is at the forefront of developing an AI-powered platform for clinical trial simulation and optimization. Our mission is to provide innovative solutions to pharmaceutical and biotechnology companies to de-risk the drug and clinical development process. We are looking for a detail-oriented Project Manager to drive operational excellence and support our data science teams in delivering innovative solutions within the clinical field. 

Key Responsibilities: 

• R&D Planning: Assist in developing and implementing operational strategies to enhance efficiency and productivity within the R&D department. Routinely collect requirements from R&D teams to aid in development prioritization and the creation of quarterly work plans. 
• Resource Management: Help oversee resource allocation, including personnel and third-part services, to ensure optimal utilization. Support resource planning by tracking team availability and project requirements. 
• Project Oversight: Help with high-level management of data science projects, ensuring they meet quality standards and deadlines. 
• Process Optimization: Identify bottlenecks and implement process improvements to enhance scalability and automation.  
• Cross-functional Collaboration: Work closely with data scientists, scientists, and engineers to help align R&D activities with the teams’ and company’s objectives. Organize meetings, workshops, and team events. 
• Reporting and Analytics: help developing tools, metrics and KPIs to monitor performance and report on R&D project progress and operational efficiency.  
• Risk Management: set up tools to Identify, monitor, and mitigate potential risks in R&D projects. 
• Documentation Management: Maintain project documentation, including reports, plans, policies and standard operating procedures. 

Qualifications: 

• Bachelor's or Master's degree in a relevant field (e.g., Industrial engineering and management, Data Science, Biomedical Engineering). 
• 3-4 years of experience in operational roles, preferably within technical and business-oriented environments. 
• Good understanding of machine learning and data science workflows in the clinical domain is a plus. 
• Proficiency with collaboration and project management tools (e.g., Slack, Asana, Confluence). 
• Strong organizational and multitasking skills. 
• Excellent verbal and written communication abilities. 
• High attention to detail and a proactive approach to problem-solving.