Data Scientist

• Identify IT & Data Science Pain Points and Define Key Success Metrics: Engage deeply with IT leaders, data scientists, and bioinformatics specialists at biotechnology companies to understand their critical pain points related to software systems, data management, and analysis, and collaboratively define key metrics to measure the success of Benchling in addressing those challenges
• Engage with Solutions Consulting Peers: Work closely with R&D and Business Value solutions consultants to ensure cohesive and comprehensive solutions are presented to customers, addressing both scientific and strategic business needs
• Design and Showcase IT Integrations and Data Pipelines: Architect and demonstrate cloud-based integrations between Benchling and other enterprise IT systems (e.g., LIMS, ELN, ERP) and develop data pipelines to facilitate data sharing, analysis, and reporting for data science teams
• Collaborate on Data Science Focused Features: Partner closely with engineers and product managers to define, prioritize, and execute on new Benchling features and integrations that specifically address the requirements of data scientists and bioinformaticians
• Enable Complex Enterprise Deployments with IT & Data Science Focus: Collaborate with Professional Services and Customer Success teams to ensure successful and scalable rollouts of Benchling at large enterprise customers, with a specific focus on integrating with their existing IT infrastructure and enabling data science (AI/ML) workflows
• Develop Targeted Messaging for IT & Data Science Audiences: Partner with Sales and Marketing to develop compelling pitches and materials that highlight Benchling's value proposition for IT departments and Data Science teams within the evolving biotechnology landscape
• Contribute to IT & Data Science Best Practices and Product Development: Participate in and contribute to initiatives focused on developing best practices for integrating Benchling within complex IT environments and shaping the product roadmap to better serve the needs of IT and data science users

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