Developer Relations Lead
TimescaleFull Time
Senior (5 to 8 years)
The ideal candidate possesses expertise in customer and field enablement, adult learning principles, educational program creation, use case architecture and implementation, and a passion for Data and AI technologies. Strong technical skills for prototyping new ideas and solutions are essential, along with a drive to ensure developer success and champion product improvements. Experience interfacing with sales teams, technical teams, customers, and potential customers is required, encompassing technical aspects of data integration, storage, access, and architectures, as well as the ability to convey complex technical concepts effectively.
The Technical Enablement Lead/Developer Relations Lead will understand the needs of various user personas, analyze their data environments, assist in designing and implementing self-service solutions, and create training artifacts to accelerate adoption. This role involves educating and inspiring the biopharmaceutical industry on the power of an open ecosystem for scientific data. Key responsibilities include setting the strategy for EU developer experience and community, managing developer discovery, onboarding, building, and scaling applications, and gathering feedback to inform product development. The role directly impacts developer adoption of TetraScience's Scientific Data & AI Cloud and innovation within the ecosystem, collaborating with Product, Engineering, Sales, and Marketing teams to empower customers and field team members through enablement programs.
Cloud platform for scientific data management
TetraScience offers a cloud-based platform called the Scientific Data Cloud, which helps biopharmaceutical companies manage and harmonize their scientific data for research and development, quality assurance, and manufacturing. The platform connects various lab instruments and software, streamlining data management and significantly reducing task completion time. TetraScience's vendor-neutral and open design allows it to work with any lab equipment, making it a flexible solution in the life sciences sector. The company's goal is to enhance scientific outcomes by preparing data for artificial intelligence and machine learning applications.