赛诺菲
特药事业部-医学信息沟通代表-绵阳
特药事业部-医学信息沟通代表-绵阳
发布于 大约 14 小时前普通员工/个人贡献者
Hyderabad, India
高级经验
全职员工
仅现场办公
本科
产品管理
AI/ML
Generative AI
Agile
Product Management
Portfolio Management
Clinical Research
AI 估算 · 250k–400k
Senior Product Owner role in AI/ML for life sciences in India; competitive salary based on experience and domain expertise.
职位详情
关于这个职位
This role leads the design, development, and adoption of AI/ML-enabled workflows for portfolio and clinical research in R&D. You will own the product roadmap, collaborate with cross-functional teams, and ensure scalable, compliant digital solutions.
最低要求
+ years of experience in Product Management or Product Ownership, preferably in life sciences, clinical research, or AI/ML environments.
Experience delivering AI-driven or analytics-driven products to scientific or clinical users.
Strong understanding of clinical development processes and portfolio governance frameworks.
Familiarity with cloud platforms (e.g., AWS) and enterprise data systems.
Solid understanding of machine learning lifecycle concepts (model development, validation, deployment, monitoring).
Experience translating data science outputs into operational workflows.
Strong ability to communicate complex AI concepts to non-technical stakeholders.
Strategic thinking with a focus on measurable research and business impact.
Proven ability to operate across scientific, technical, and operational domains.
Comfortable managing ambiguity in emerging AI use cases.
Bachelor’s or Master’s degree in Data Science, Bioinformatics, Computer Science, Clinical Research, or related field.
工作职责
Product Ownership:
Own the roadmap and backlog for Portfolio & Clinical AI workflows.
Define use cases and requirements for AI/ML-driven analytics, decision-support tools, and automated workflow capabilities.
Translate scientific, clinical, and portfolio needs into clear product specifications.
Ensure workflows are production-ready, compliant, and aligned with enterprise standards.
AI Workflow Design & Enablement:
Partner with data scientists to operationalize machine learning and generative AI models into reproducible workflows.
Define integration patterns between AI models, enterprise data systems, and workflow execution environments.
Ensure traceability, reproducibility, and auditability of AI-driven outputs in regulated contexts.
Stakeholder & Cross-Functional Collaboration:
Collaborate with clinical development teams, portfolio strategy and governance stakeholders, data science and AI engineering teams, platform and infrastructure partners.
Align workflow priorities with portfolio milestones and clinical development timelines.
Proactively manage dependencies on underlying data and workflow platforms.
Delivery & Execution:
Lead agile development cycles in partnership with engineering and Scrum teams.
Maintain a prioritized backlog that balances short-term impact with long-term workflow scalability.
Define success metrics tied to adoption, efficiency gains, and scientific outcomes.
Oversee pilot launches, iteration cycles, and scaling of successful workflows.
Continuous Improvement & Impact Measurement:
Track adoption, usability, and scientific impact of deployed AI workflows.
Gather feedback from clinical and portfolio users to refine capabilities.
Identify new AI opportunities aligned with strategic research priorities.
优先资格
Familiarity with data engineering, APIs, and workflow orchestration environments is a plus.
Understanding of compliance and audit requirements in regulated research settings is preferred.
Advanced degree (Ph.D., M.D., or equivalent) in a scientific or clinical discipline is a plus.
AI 洞察
优缺点分析
优点
- You work at the cutting edge of AI in drug development, a high-impact area.
- Role combines technical depth with strategic product ownership, offering strong career growth.
- Collaboration with diverse teams (scientists, engineers, executives) builds a broad network.
- Requires deep domain knowledge in clinical research
- steep learning curve if from non-life-science background.
- Managing ambiguity in emerging AI use cases can be demanding.
- Regulatory compliance adds complexity to product delivery.
- This role is ideal for a product manager with strong technical AI understanding who thrives at the intersection of science and technology.
缺点 / 挑战
暂无明显挑战项
角色解读
- Progress to Head of Digital Products or Director of AI Solutions in R&D.
- Specialize further in AI product strategy or move into senior leadership roles.
- Expand into broader digital transformation roles across pharmaceutical R&D.
- You own the product roadmap and backlog for AI-powered workflows in portfolio and clinical research.
- You collaborate with data scientists, clinical teams, and engineers to translate scientific needs into production-ready digital solutions.
- You define success metrics and drive adoption of AI workflows across R&D.
- Solid understanding of machine learning lifecycle (model development, validation, deployment).
- Experience in product management within life sciences or clinical research.
- Ability to communicate complex AI concepts to non-technical stakeholders.
- Familiarity with cloud platforms like AWS and enterprise data systems.
申请策略
- Tailor your cover letter to show understanding of R&D pain points in pharma.
- Mention familiarity with compliance standards like 21 CFR Part 11 if applicable.
- Emphasize experience owning AI/ML product roadmaps and delivering to scientific users.
- Highlight any work in regulated environments (e.g., pharma, healthcare).
- Showcase measurable impact metrics (adoption rates, efficiency gains).
- Deepen knowledge of clinical development processes (e.g., ICH guidelines, GCP).
- Learn workflow orchestration tools (e.g., Apache Airflow, Kubeflow).
面试指南
- Use the STAR method (Situation, Task, Action, Result) to structure responses.
- For product ownership questions, emphasize user research, backlog management, and stakeholder alignment.
- Can you describe a time you translated a scientific requirement into a product specification?
- How do you prioritize features when dealing with multiple stakeholders from clinical and data science teams?
- Explain how you would measure the success of an AI workflow in a regulated environment.
- How do you ensure reproducibility and auditability of AI-driven outputs?
- Describe your experience with agile development in a cross-functional team.
- Review common clinical research phases and portfolio governance frameworks.
职位点评
70
综合评分
Senior AI product role in pharma R&D, strong tech stack, growth-oriented, but on-site and moderate WLB.
更适合这类人
This role is best for candidates driven by cutting-edge technology and career growth in AI for life sciences, who are comfortable with on-site work and some ambiguity.
表现最好
成长发展
相对薄弱
工作生活
薪资福利70
成长发展85
工作生活50
使命价值75
薪资福利
70中等
Salary is competitive for senior AI product roles in India, but not explicitly stated in JD. Benefits not mentioned.
薪资信号未披露（AI估算：250K-400K/月）
成长发展
85较高
Strong focus on AI/ML and cutting-edge technology; clear growth path in R&D digital transformation.
技术前沿前沿/新兴技术
技术栈AI/ML、Generative AI、AWS、Workflow Orchestration
成长机会product ownership、lead agile development cycles、continuous improvement
业务类型profit_center
工作生活
50较低
On-site in Hyderabad; no mention of flexible work or WLB. Likely standard office hours with some flexibility.
工作模式仅现场办公
办公地点未明确
加班情况未提及（无法判断）
使命价值
75中等
Pharma R&D contributes to healthcare, but role is more technology-driven. Moderate social impact.
行业发展高速增长赛道
社会影响中性/一般
创新程度积极采用新技术
Watch Jobs