About this opportunity
关于此角色:我们正在寻找一名生成式AI及数据科学负责人,负责将商业化、医学及生命科学相关业务痛点转化为可落地的机器学习与生成式AI解决方案,帮助业务团队提升决策质量、运营效率与客户体验。在这个岗位上,您将主导企业级知识库、检索增强生成(RAG)、智能搜索、AI助理及智能工作流等能力建设,推动AI从单点工具走向可治理、可复用、可规模化创造业务价值的能力体系。该岗位将与业务、数据、工程、IT、合规、法务及外部供应商紧密协作,并向数据科学与生成式人工智能负责人汇报。
主要职责:• 负责将商业化、医学及生命科学相关业务痛点转化为清晰的机器学习或生成式 AI 技术路径、产品需求和中长期能力路线图。• 深入商业化、医学及生命科学业务场景,与业务团队共同澄清高价值问题,将模糊需求快速转化为可执行的 AI/ML 技术方案,并通过原型开发、PoC、业务验证和生产部署实现端到端交付。• 主导企业级知识库、检索增强生成(RAG)、智能搜索、记忆系统及可复用数据管道建设,覆盖知识架构设计、文档处理与索引策略、元数据与权限管理、数据资产复用、评估集建设、质量监控、内容治理及持续运营机制。• 负责生成式 AI 应用的算法原型设计、效果调优、模型评估和能力迭代,结合大语言模型、提示词工程、知识图谱、推荐系统、因果推断、深度学习或多智能体框架等技术,并在准确性、延迟、成本、可追溯性和用户体验之间做工程权衡,形成稳定、可扩展、可追溯的企业级解决方案。• 建立企业级 AI 工程化与标准化框架,包括模型评估指标体系、精调流程、部署与监控规范、质量追踪、风险控制和合规评估方案,确保 AI 能力在医药行业场景中安全、合规、稳定地运行。• 与业务、数据、工程、IT、合规、法务及外部供应商紧密协作,管理跨职能团队预期和交付节奏,向高层清晰传达技术价值、业务影响和投资回报(ROI),推动 AI 文化和标准化工作流程在业务端落地。基本要求:• 硕士及以上学历,计算机科学、人工智能、机器学习、数据科学、统计学、数学、信息管理或相关专业优先。• 5年以上人工智能、机器学习、生成式 AI、数据科学、企业级 AI 产品或平台工程相关经验。• 具备扎实的前沿算法与模型能力,熟悉大语言模型(LLM)应用及微调方法,包括监督微调(SFT)、强化学习(RL/RLHF)、提示词工程、多智能体协同框架,并了解知识图谱、推荐系统、因果推断、深度学习、多模态 AI 等交叉技术。• 具备生产级 AI 工程化和标准化能力,熟悉模型评估指标、精调流程、数据管道、知识库与记忆系统设计、部署监控、质量治理、可追溯性管理及生产级系统稳定性要求。• 具备优秀的业务理解与技术翻译能力,能够将复杂业务问题拆解为可执行的功能、数据需求和系统方案,平衡技术投入、业务价值、成本效率和投资回报(ROI),并能整合内外部数据资源与合作伙伴生态。• 具备优秀的跨职能项目管理、沟通表达和高层影响力,能够协调业务、数据、工程、合规、法务及供应商团队,在复杂环境中建立标准化流程,推动 AI 文化落地,并持续提升团队创新能力。理想要求:• 具备医疗、生命科学、医药商业化、咨询或企业级数字化转型经验者优先。• 具备从算法原型、效果调优、工程部署到持续迭代的完整项目经验者优先。
Job details
How this role compares
Computed from every other active Sales role in our database, not just this employer's listings.
We currently track 2393 comparable Sales roles across 138 biopharma companies.
Salary context
636 of 2393 peers report a salary range (USD, annualized)
Peers share this role's job function. This posting doesn't list a seniority level, so peers aren't narrowed by seniority either -- the range below may span more levels than usual.
Where these roles are based
Top locations among the 2393 comparable roles
+ 59 more countries
Seniority mix
956 of 2393 peers have a known seniority level
Therapeutic area mix
651 of 2393 peers have a known therapeutic area; the rest are genuinely unlabeled, not hidden
Similar opportunities
The closest matches from our peer group, ranked by how similar they are, not how well you'd qualify for them -- treat this as market context, not a guaranteed shortlist; a weak match is labeled as one below.
Open in 2 locations
Open in 2 locations
How we calculate "similar"
No black box, no LLM guesswork: a deterministic score built from four normalized attributes. Here's this role's own peer group at different match levels, so you can see the mechanism, not just the result.
Every comparison starts from the same 100-point budget: 25 for working in the same function, 40 for the same therapeutic area, 20 for the same or adjacent seniority, 15 for the same country. A dimension we can't confirm on both sides contributes nothing, never a guess, never a free pass.
0 points, never a partial guess. A role we know almost nothing about beyond its function bottoms out at 25%; it never inflates to 100% just because there's little to compare against. Seniority uses a defined ladder (Associate → Manager → Associate Director → Senior → Principal → Director → Senior Director → Executive/VP) so "Director" and "Senior Director" count as adjacent, but "Director" and "Executive/VP" do not.