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Product Owner for AI & Molecular Modeling
Product Owner for AI & Molecular Modeling
发布于 4 天前中层管理(经理/总监)
Cambridge, Massachusetts
高级经验
全职员工
仅现场办公
本科
产品管理
Machine Learning
Agile
Product Management
Cadd
Molecular Modeling
AI 估算 · 80k–120k
海外AI制药产品经理，薪资基于行业经验和市场水平，结合职位要求较高，预估月薪80K-120K人民币。
职位详情
关于这个职位
As a Product Owner for AI & Molecular Modeling at Sanofi, you will lead the vision and execution of AI/ML-driven digital products that bridge computational predictive models with medicinal chemists. You will define product strategy, prioritize features, and manage agile cross-functional teams to deliver tools that accelerate small molecule drug design. This role combines deep technical knowledge in CADD and AI with user-centered product management, directly impacting how scientists leverage computational insights.
最低要求
Bachelor's degree in Life Sciences, Computational Chemistry, Molecular Modeling, Cheminformatics, Biochemistry, Medicinal Chemistry or a related field. Master's or PhD degree is a plus but not a must.
+ years of experience in product ownership and translating scientific business requirements into technical specifications.
Proven track record of leading cross-functional agile teams in a scientific or R&D environment.
Demonstrated experience delivering digital products with measurable scientific or operational impact.
Hands-on experience with AI/ML, molecular modeling, or CADD methodologies in a drug discovery context.
Experience defining and tracking product KPIs and communicating results to executive stakeholders.
工作职责
Lead agile and iterative product development in cross-functional pods with data scientists, ML engineers, UX/UI designers, and data engineers.
Define detailed user stories, acceptance criteria, and success metrics grounded in scientific workflows.
Coordinate with MLOps and data engineering teams to validate technical requirements and architecture decisions.
Ensure delivered products are scientifically rigorous, scalable, and accessible to non-computational scientists.
Drive continuous improvement cycles based on user feedback and adoption data.
Define, establish, and monitor KPIs and success metrics to demonstrate product value and return on investment.
Build and present executive-level reports and dashboards communicating product progress, adoption metrics, and value delivered.
Translate complex technical and scientific outcomes into clear business impact narratives for senior leadership.
Conduct regular product reviews with stakeholders to assess performance against strategic objectives.
Proactively identify and communicate risks, trade-offs, and mitigation strategies to leadership.
Coordinate and align cross-functional agile teams including data scientists, ML engineers, computational chemists, and UX designers.
Build partnerships with R&D scientists to deeply understand small molecule discovery workflows and pain points.
Collaborate with the Product Line Owner on portfolio strategy, prioritization, and resource allocation.
Facilitate co-creation workshops, sprint planning, and backlog refinement sessions.
Manage trade-offs between user needs, technical feasibility, and strategic priorities across stakeholders.
Conduct user research with molecular design scientists to understand workflows, data needs, and predictive modeling requirements.
Design intuitive interfaces and visualizations that make AI/ML predictions accessible, interpretable, and actionable.
Lead usability testing sessions and gather continuous feedback from scientist users.
Drive product adoption through targeted training, documentation, and change management initiatives.
Monitor adoption metrics and iterate on solutions to maximize engagement and scientific impact.
Serve as the primary translator between AI/ML and molecular modeling technical capabilities and scientific user needs.
Maintain deep knowledge of CADD methodologies (molecular docking, molecular dynamics, QSAR, free energy perturbation, pharmacophore modeling) to make informed product decisions.
Stay current on emerging AI/ML approaches in drug discovery, including generative molecular design, structure-based AI, and multi-parameter optimization.
Collaborate with data engineers to ensure robust data pipelines and APIs support seamless user experiences.
Ensure proper integration with existing molecular design tools, cheminformatics platforms, and scientific databases.
优先资格
Hands-on experience with python-based libraries for molecular manipulation (RDKit, OpenBabel, DeepChem) and vizua (truncated).
AI 洞察
优缺点分析
优点
- Cutting-edge work at the intersection of AI and drug discovery, with high impact on real-world medicines.
- Strong company reputation (Sanofi) and resources of a large biopharma, providing stability and growth opportunities.
- Opportunity to work with world-class scientists and engineers, building a valuable network.
- High expectations and fast-paced environment in R&D digital transformation.
- Need to constantly learn and adapt to rapidly evolving AI/ML technologies.
- Balancing scientific rigor with agile product development can be demanding.
- This role is ideal for an experienced product manager with a strong scientific background in computational chemistry or AI, who enjoys bridging technical and business domains and driving innovation in a mission-driven organization.
缺点 / 挑战
暂无明显挑战项
角色解读
- Progress to Senior Product Owner or Head of Product for Digital R&D, leading a portfolio of AI products.
- Transition to a more strategic role like Director of Digital Innovation or VP of Product in biopharma.
- Opportunity to become a domain expert in AI-driven drug discovery, influencing industry-wide practices.
- Define product vision and strategy for AI/ML tools that assist medicinal chemists in molecular design and optimization.
- Manage a backlog of user stories and prioritize features based on scientific impact and user needs.
- Lead cross-functional agile teams including data scientists, ML engineers, and UX designers to deliver iterative product releases.
- Measure and communicate product success through KPIs and executive-level reporting.
- Deep understanding of CADD methods (molecular docking, MD, QSAR) and AI/ML applications in drug discovery.
- Strong product management skills: backlog management, stakeholder communication, agile methodologies.
- Ability to translate complex computational concepts into intuitive user experiences.
- Excellent presentation and communication skills to bridge scientific and business stakeholders.
申请策略
- Tailor your cover letter to explain how your product management experience directly accelerated scientific discovery.
- Research Sanofi's digital R&D initiatives and mention specific areas where you can contribute.
- Emphasize experience with AI/ML in drug discovery, especially small molecule projects.
- Highlight product management achievements with measurable impact (e.g., KPIs, adoption rates).
- Showcase knowledge of CADD tools and cheminformatics libraries (RDKit, etc.).
- Include examples of leading cross-functional agile teams and managing stakeholder communications.
- Strengthen understanding of generative molecular design and structure-based AI.
- Familiarize with product analytics tools and frameworks for measuring scientific productivity.
面试指南
- Use the STAR method (Situation, Task, Action, Result) for behavioral questions.
- For technical translation questions, break down complex concepts into simple analogies and focus on user benefit.
- For prioritization, mention frameworks like RICE or value vs. effort, and tie back to scientific impact.
- How do you prioritize features when scientific needs conflict with technical feasibility?
- Describe a time you led a cross-functional team to deliver a complex scientific product. What was the outcome?
- How would you measure the success of an AI-powered molecular design tool?
- Explain CADD methods like free energy perturbation to a non-scientist executive.
- How do you ensure user adoption for new digital tools in a research environment?
匹配度报告
74
综合匹配度
High-growth AI product role in biopharma with strong developmental and purposive rewards, moderate compensation disclosure, and standard on-site expectations.
适合人群
This role is best suited for professionals motivated by cutting-edge technology and career growth, who are willing to trade off some work-life balance for high impact in drug discovery.
最强匹配
成长发展匹配
最弱匹配
工作生活匹配
薪资福利70
成长发展90
工作生活50
使命价值85
薪资福利匹配
70中等
The position offers competitive compensation typical of a senior product role in a top biopharma, but exact figures are undisclosed. Benefits are not detailed in the JD, so the signal is neutral.
薪资信号未披露（AI估算：80K-120K/月）
成长发展匹配
90较高
This role sits at the forefront of AI in drug discovery, offering continuous learning in cutting-edge technologies like generative molecular design and structure-based AI. The company provides opportunities to grow as a product leader in digital R&D.
技术前沿前沿/新兴技术
技术栈AI、Machine Learning、Molecular Modeling、CADD、Generative Molecular Design、Structure-based AI
成长机会agile product development、cross-functional team leadership、executive-level reporting、user research
业务类型profit_center
工作生活匹配
50较低
The role is based in Cambridge, MA, likely requiring on-site presence. No mention of remote flexibility or WLB initiatives. The fast-paced R&D environment may demand extended hours.
工作模式仅现场办公
办公地点市区核心地段
加班情况未提及（无法判断）
使命价值匹配
85较高
Working on AI for drug discovery directly contributes to developing life-saving medicines, providing strong sense of purpose. Sanofi's mission-driven culture amplifies the positive social impact.
行业发展高速增长赛道
社会影响正向社会影响力较高
使命信号chase the miracles of science to improve people's lives、transform the practice of medicine
创新程度积极采用新技术
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