Product Manager - Clinical Coding, Revenue Cycle, AI
Summary
Nym is hiring a Product Manager in Tel Aviv to own initiatives for its AI-powered autonomous clinical coding engine. The role bridges product, clinical coding (ICD-10-CM, CPT/HCPCS), and engineering — translating ambiguous coding and customer problems into requirements, metrics, and production rollouts alongside R&D and AI research teams.
Nym is a healthcare technology company transforming clinical coding through AI. Our autonomous coding engine interprets clinical documentation and applies clinical and coding knowledge to accurately code patient encounters at scale.
We are looking for an experienced Product Manager to join our Product team in Israel and work closely with our R&D and AI Research teams.
This role sits at the intersection of product, clinical coding, AI, and engineering. You will translate complex clinical coding and customer problems into clear product and technical requirements, work with R&D and Applied Research to design scalable solutions, and own initiatives from problem definition through development, validation, and production rollout.
The ideal candidate is highly analytical, technically strong, comfortable working with complex AI-driven systems, and able to turn ambiguous problems into structured product decisions.
In this role, you will:
- Own product initiatives related to Nym's autonomous clinical coding engine, from problem definition through production rollout and measurement.
- Develop a deep understanding of clinical coding workflows, including ICD-10-CM, CPT/HCPCS, coding guidelines, clinical documentation, and healthcare billing requirements.
- Translate clinical coding, customer, and business problems into clear product requirements and technical specifications.
- Analyze engine behavior, coding results, customer data, and production performance to identify product gaps and improvement opportunities.
- Define success metrics and acceptance criteria, and validate that delivered solutions achieve the expected product and coding outcomes.
- Break complex problems into initiatives, epics, requirements, and user stories that enable effective R&D execution.
- Own and prioritize the backlog within your product area, balancing accuracy, automation coverage, scalability, technical investment, customer impact and market impact.
- Partner with coding and compliance experts to translate coding guidelines and regulatory requirements into scalable AI-driven solutions.
- Ensure new capabilities are measurable and observable in production, with appropriate monitoring and performance metrics.
- Communicate product decisions, tradeoffs, progress, and results clearly to both technical and non-technical stakeholders.
Requirements
- 4+ years of Product Management experience working on complex software or data products.
- BSc in Computer Science, Engineering, Information Systems, or equivalent technical experience.
- Demonstrated ability to work closely and effectively with engineering teams on technically complex products.
- Strong analytical and problem-solving skills, including the ability to investigate data, understand system behavior, and identify root causes.
- Experience translating ambiguous business or domain problems into structured product and technical requirements.
- Strong understanding of software development processes and Agile product development.
- Experience defining product metrics, acceptance criteria, and data-driven measures of success.
- Ability to understand complex systems and make thoughtful tradeoffs between product value, technical complexity, scalability, and time to market.
- Excellent written and verbal communication skills in English.
- Ability to operate effectively in a fast-moving environment with significant ambiguity and evolving requirements.
Strong Advantages
- Experience building AI/ML, NLP, LLM, or other data-driven products.
- Experience working with healthcare technology, clinical data, or medical records.
- Familiarity with medical coding, or revenue cycle workflows.
- Experience with enterprise SaaS products and complex customer integrations.
- Experience defining or evaluating AI quality, including concepts such as accuracy, precision/recall, confidence, evaluation datasets, and production monitoring.
- Experience working with large datasets and using analytical tools to investigate product behavior.