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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in shaping and executing strategic enterprise opportunities within the pharma and biotech sectors, leveraging AI and data solutions. Capable of leading cross-functional discussions, translating complex demands into scalable solutions, and driving executive decision-making.
Highest-signal resume keywords
Pharma R&D WorkflowsAI and Data IntegrationEnterprise Solutions StrategyStakeholder EngagementTechnical Solution Design
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
AI ApplicationsData PlatformsAPIsSystem IntegrationsSolution ArchitectureData GovernanceIntegration PatternsKnowledge GraphsPilot DesignScoping Frameworks
Soft Skills
Executive Decision-MakingJudgment in RecommendationsCommunication SkillsProblem-SolvingCollaboration
Certifications & Qualifications
Advanced Degree in Science or Quantitative Field
Industry Keywords
PharmaBiotechLife SciencesB2B SaaSRegulated EnvironmentMarket ExpansionEnterprise CustomersGrowth OpportunitiesCommercial StakeholdersEngagement Manager
About the role
Key responsibilities & impact- Incubate and validate new growth opportunities across AI, data, product, and pharma and biotech customers
- Own intake and shaping of strategic enterprise opportunities requiring new capabilities, integrations, packaging, or market positioning
- Drive executive decisions on whether to pursue, park, or decline opportunities
- Lead senior pharma R&D and commercial stakeholder discussions and translate ambiguous demands into scalable solution paths
- Define target states, success criteria, constraints, scope boundaries, sequencing, timelines, risks, dependencies, and mutual commitments
- Shape commercial framing and scalable commitments
- Design and steer technical solutions involving platform capabilities, APIs, data models, integrations, security, and deployment models
- Work with Engineering and Data teams through build, testing, and deployment without writing production code
- Evaluate technical feasibility, architectures, integration and data risks, configuration versus build requirements, and effort
- Shape and evaluate technology partnerships
- Represent Causaly’s platform and roadmap in executive and technical forums
- Build repeatable solution playbooks for R&D and commercial workflows, including offerings, use cases, packaging, qualification, scoping, delivery blueprints, reference architectures, and enablement assets
- Standardize Private Data, enterprise integrations, and AI workflows into productized motions
- Co-sponsor lighthouse opportunities with Sales to validate solution plays
- Orchestrate pilot design, governance, and decisioning for transferable and repeatable solutions
- Hand validated plays into Sales, Customer Success, Delivery, and Product with training, assets, decision trees, and ownership clarity
- Maintain feedback loops into Product on product candidates, investments, and enterprise-demand constraints
Requirements
What you’ll need- 7+ years’ experience at the intersection of pharma or life sciences strategy, AI and data, and enterprise customers
- Track record of leading discussions with senior R&D and commercial stakeholders and shaping ambiguous asks into scalable solutions
- Background in life science strategy or AI consulting at Engagement Manager / Associate Partner level, or enterprise solutions / solutions strategy in B2B SaaS serving pharma and biotech
- Deep understanding of end-to-end pharma R&D and commercial workflows and related decisions
- Hands-on experience building, deploying, and/or integrating enterprise technology solutions, including data platforms, AI and LLM applications, APIs, and system integrations
- Ability to read and challenge solution architectures and reason through data pipelines, APIs, integration patterns, and AI/LLM systems
- Understanding of retrieval-augmented generation, agentic workflows, and knowledge graphs
- Experience turning complex enterprise demand into repeatable playbooks, including qualification criteria, scoping frameworks, pilot design, and BAU handoff
- Strong judgment in pursue / park / decline recommendations based on product direction, feasibility, scalability, and business impact
- Comfort driving executive decision-making across Product, Engineering, and GTM and translating technical trade-offs into business choices
- Scientific or quantitative background, advanced degree, AI/GenAI pharma programme experience, technical capacity, regulated-environment data governance, or market expansion experience are nice to have
- Must be able to work from the office 4 days per week
- Must answer whether visa sponsorship is required to work in the UK