分析工程师
Software Engineer, Analytics
软件工程师，分析
简介
- 我们是一家早期创业公司，致力于通过为医生、护士和护理团队提供实时数据，使医疗保健更加主动，以挽救生命。
- 你将负责开发我们的临床AI/ML产品分析基础设施、框架和工具，使我们的客户成功、产品、临床和技术团队能够通过更好的洞察力提升决策水平。
我们是谁
Bayesian Health 的使命是通过为临床医生提供他们需要的见解，在诊疗过程中为正确的患者做出正确的决策，从而改善患者结果。我们是一支多元化的团队，包括临床医生、工程师、机器学习专家、产品设计师和绩效改进领导者，致力于通过解锁数据的力量，实现更智能、更个性化的护理交付。
我们获得了顶级科技和生物科技投资者的支持：Obvious Ventures、Andreessen Horowitz、美国医学协会风险投资部门、Catalio Partners 和 LifeForce Capital。我们的公司获得过许多奖项；最近的荣誉包括：福布斯 AI 50 强、世界经济论坛科技先驱、时代最佳发明、生物技术 AI 年度公司。
了解更多关于我们在《自然医学》上发表的最新论文，该论文将我们的产品与挽救的生命联系起来。
你会做什么
作为高级软件工程师，分析，你将与客户成功团队、产品经理、临床医生、数据科学家和其他软件工程师紧密合作，构建基础设施、框架和工具，以提高客户分析能力，促进临床案例审查，并支持产品调查。这个角色对于提供产品性能的内部可见性至关重要，这将推动我们临床 AI/ML 模块产品的扩展和收入增长。
职责
- 产品性能监控和优化：与客户成功和临床产品主题专家合作，实施基础设施、查询和自动化工具，以监控我们多个临床领域和客户的产品 KPI 和成功指标。
- 临床案例审查和调查：构建框架和工具，使我们的临床团队能够独立审查和调查客户报告的临床案例，并识别需要进一步评估的特定标准的案例。
- 数据平台和分析技术基础：提出并实施基础改进和创新，以提升我们的数据平台。
查看英文原文
Software Engineer, Analytics
In Brief
- We’re an early-stage startup on a mission to make healthcare proactive by empowering physicians, nurses, and care team members with real-time data to save lives.
- You will lead the development of our clinical AI/ML product analytics infrastructure, frameworks, and tools to enable our client success, product, clinical, and technology teams to uplevel our decision making through better insights.
Who We Are
Bayesian Health’s mission is to improve patient outcomes by empowering clinicians with the insights they need to make the right decision for the right patient at the point-of-care. We’re a diverse team of clinicians, engineers, machine learning experts, product designers, and performance improvement leaders committed to enabling smarter, patient-specific care delivery through unlocking the power of data.
We’re funded by top tier tech and biotech investors: Obvious Ventures, Andreessen Horowitz, American Medical Association’s venture arm, Catalio Partners, and LifeForce Capital. Our company has won many awards; most recent recognitions include: Forbes AI Top 50, World Economic Forum Tech Pioneer, Time Best Inventions, BioTech AI Company of the Year.
Read more about our recent publication in Nature Medicine that associates our products with lives saved.
What you'll do
As a Senior Software Engineer, Analytics, you will work closely with client success, product managers, clinicians, data scientists, and other software engineers to build infrastructure, frameworks, and tools to improve client analytics, facilitate clinical case reviews, and support product investigation. This role is crucial to provide internal visibility into product performance that will drive expansion of our clinical AI/ML module offerings and revenue growth.
Responsibilities
- Product performance monitoring and optimization: Partner with client success and clinical product subject matter experts to implement the infrastructure, queries, and automation to monitor the KPIs and success metrics of our products across multiple clinical domains and clients.
- Clinical case review and investigation: Build frameworks and tools to empower our clinical team to independently review and investigate clinical cases reported by our clients and identify cases with certain criteria that need further evaluation.
- Data platform and analytics technical foundations: Propose and implement foundational improvements and innovations to boost our data platform scalability with expanding products and clients and uplevel our team analytics capabilities.
- Drive product analytics development cross-functionally: Work closely with Client Success, Clinical, Product, Data Science, and Engineering to drive alignment on product analytics at the company level.
Minimum qualifications
- BS in Computer Science or other relevant technical discipline.
- 5+ years of experience in building scalable, secure analytics infrastructure and tools on a cloud platform (preferably AWS) to produce monitoring metrics and investigational data from complex data models and queries for live products and customers.
- Proficient in Python and SQL.
- Deep knowledge in modern data and analytics technologies, such as cloud-based data warehouses, transformation frameworks (e.g. dbt), workflow orchestration tools, and BI tools like Tableau or Quicksight, and keen ability to integrate with existing infrastructure to enhance capabilities.
- Experience working with sensitive data that contains PHI/PII.
- Excellent communication skills and a proven ability to collaborate with cross-functional teams (data science, product, clinical) to translate requirements into robust technical solutions
Preferred qualifications
- Experience in leveraging LLMs in distributed data processing and analytics systems.
- Experience building analytics technology for clinical/health data.
- Experience handling ambiguity and uncertainty in a startup.
Bayesian Health provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.
This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation and training.