China MLS Publisher - Open Access & Growth Lead

Sage; Shanghai (VA); Híbrido; USD 110.000 - 170.000; Jornada completa

Descripción de la vacante

Sage is seeking a Publisher to lead its Medicine & Life Sciences portfolio in China, driving growth in MLS journals and managing partnerships with external editors and institutions. The role involves building a China-focused OA program, guiding editorial strategy, and expanding the team in line with strategic plans and market opportunities.

As a key representative for Sage in China, you will mentor the editorial team, coordinate with global colleagues, and shape commercial strategies to maximize

Formación

• Extensive experience leading journals publishing in China.
• Proven track record launching Chinese partner journals in Medicine & Life Sciences.
• Strong financial acumen and profitability track record.
• Excellent relationship management and negotiation skills.

Responsabilidades

• Identify journal launch and local Chinese partnership opportunities to achieve targets and grow OA portfolio.
• Develop and execute editorial strategy for a significant portfolio of journals.
• Build and maintain relationships with learned societies, editors and boards.
• Oversee contract negotiations and renewals, guiding financial decisions.
• Prepare and review profit and loss statements in line with Sage's commercial goals.

Conocimientos

Journals publishing in China

Open access publishing

Partnership development

Editorial leadership

Herramientas

Microsoft Office

Descripción del empleo

Sage is seeking a Publisher to lead its Medicine & Life Sciences portfolio in China, driving growth in MLS journals and managing partnerships with external editors and institutions. The role involves building a China-focused OA program, guiding editorial strategy, and expanding the team in line with strategic plans and market opportunities.

As a key representative for Sage in China, you will mentor the editorial team, coordinate with global colleagues, and shape commercial strategies to maximize