Covidence.org

• Lead the next stage of marketing evolution at Covidence • Help researchers, institutions and review teams better understand Covidence and evidence synthesis • Oversee marketing across positioning, content, product marketing and demand generation for institutional and practitioner audiences • Work closely with Product, Revenue, Community and Leadership teams • Create greater clarity in the market about where Covidence fits and why it matters • Build trust and confidence in Covidence’s approach to AI and evidence synthesis • Increase Marketing’s contribution to enterprise engagement, pipeline and customer growth • Establish more effective collaboration between Marketing, Product, Revenue and Community teams • Help the organization use Marketing more strategically to strengthen customer understanding and market trust • Build necessary capabilities for the next stage of growth in a lean, highly collaborative organization

• Provide strategic guidance and oversight of the Foundation’s mission, programs and impact • Ensure high standards of governance, risk management and regulatory compliance • Oversee financial sustainability, including budgets, funding strategies and major investments • Support and constructively challenge the executive team on key decisions • Act as an ambassador for the Foundation, leveraging networks to advance our mission • Participate actively in Board and committee meetings • Serve on at least one Board subcommittee (to be established in the next 12 months)

• Identify training solutions to develop research skills in evidence synthesis process and methods • Plan and deliver user training for customer organisation and the wider review community • Provide subject-matter expertise and technical demonstrations as part of the pre-sales process • Represent Covidence at events and conferences • Provide fast, expert support to users via email and live chat • Create and maintain support and educational resources

• Collaborate with the product and engineering team to identify areas for automation and improvement • Designing and developing state-of-the-art NLP algorithms, with a focus on orchestrating LLMs across various providers (OpenAI, Anthropic, Google, etc.) to optimize for cost, latency, and accuracy. • Analyse data and conduct experiments to improve the accuracy and efficiency of models • Build and deploy models that can be integrated into production applications • Evaluate emerging LLM tools and frameworks to maintain a competitive edge in research automation • Collaborate with leading ML practitioners in the research synthesis space to fundamentally change the way the world derives accurate insights from global research output