ConvergeHEALTH - R&D Life Sciences, Product Owner - Innovation_Delivery_Transformation
- Act as the functional SME, bringing real-world knowledge from pharma R&D lab environments and end-to-end lab workflows (across multiple R&D domains) to define product requirements; partner with Product Management to translate those requirements into user stories, acceptance criteria, and key edge cases.
- Provide cross-domain perspective across pharma R&D (discovery through development; adjacent handoffs as relevant), ensuring features support common workflows rather than narrow, single-technique needs.
- Recommend workflow improvements for efficiency, quality, and compliance, and translate them into product features and configuration options
- Define expected data outputs and end-to-end flows (sources, formats, and metadata expectations) to inform ingestion, standardization, traceability, and downstream use cases.
- Leverage expertise in lab data types (e.g., assay data, imaging data, multi-omics data) to inform product data models, integration patterns, and functional capabilities.
- Provide functional leadership and best practices for managing lab data across diverse instruments and platforms (including practical realities like missing metadata, versioning, reprocessing, and auditability)
- Partner day-to-day with Product Management, Engineering, UX, and QA to clarify intent, review designs, validate workflow fit, and support release readiness.
- Create, curate, or source open datasets (and/or realistic synthetic datasets where needed) that represent common lab outputs for functional testing, demos, and regression coverage.
- Define test scenarios that reflect real lab behavior (repeats, controls, reruns, calibration drift, batch effects, exceptions) and ensure the product handles them reliably.
- Contribute to ongoing product research and development efforts by tracking emerging trends in lab informatics, data science, and digital transformation that affect product direction
- Knowledge of automation and AI/ML applications in lab informatics and/or experience with digital transformation initiatives focused on laboratory environments
- Act as a product owner, in context of product forward deployed engineer (pFDE) pod deployed on client engagements to make the engagement successful and remove any friction in adoption of product
- Support client-facing activities during sales cycles, including participating in demos and drafting the demo storyline to highlight the product's strongest capabilities and value proposition
- Pursuit support, helping shape use-case framing, respond to workflow/technical questions, and address objections with credible lab-domain context
- Bring insights from your experience (and structured internal feedback loops with SMEs/users) back to the product team to inform and influence the product roadmap
- Demonstrated ability to translate domain knowledge into crisp functional requirements and to collaborate effectively in a techno-functional product environment
- Quick learner, ability to pick the rapid AI prototyping tools (Cursor, Lovable, N8N, ElevenLabs) to convert ideas to demonstrable concepts
- Bachelor's degree (Master's preferred) in computational biology, bioinformatics, life sciences, biomedical engineering, or a related field
- 6+ years of experience working in or closely supporting biotech/pharma R&D labs (lab operations, lab informatics, scientific data systems, or similar)
- 3+ years of hands-on experience with LIMS and/or ELN platforms and how they fit into scientist workflows
- 2+ years of experience working with laboratory workflows, instruments, and data modalities (e.g., flow cytometry, genomics, proteomics, imaging, or other analytical tools)
- Ability to travel up to 25%, on average, based on the work you do and the clients and industries/sectors you serve
- Must be legally authorized to work in the United States without the need for employer sponsorship, now or at any time in the future
- 2+ years of experience integrating lab instruments and data systems to streamline workflows and enable cross-platform data use
- 1+ year of exposure to AWS or cloud-native concepts and modern data/analytics patterns
- 1+ year of experience in regulated lab environments with familiarity of compliance expectations (e.g., GxP, 21 CFR Part 11), including audit trails, e-signatures, and validation-ready documentation
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