Zelis is modernizing the healthcare financial experience across various stakeholders. They are seeking an AI Product Manager to oversee the product lifecycle of new AI solutions, collaborating closely with data science and engineering teams to deliver on the product roadmap.
Responsibilities:
- Become an expert in your product areas, acting as the go to person for other stakeholders before speaking to the technical data science and software engineering teams
- Collaborate with software engineers, data engineers, data scientists and other product teams to scope new or refine existing AI solutions that increase business value, adoption, and user engagement
- Lead discussions with BU stakeholders to identify business process and underlying needs. Draft clear and concise business requirements and technical product documentation
- Interface with internal to Zelis engineering and product teams to manage the intake process for new requests
- Understand how your product areas link into the wider roadmap and be able to highlight both dependencies and opportunities for growth
- Define key performance indicators to evaluate product
- Be the voice of the customer in technical discussions and facilitate the relationship between the application teams and technical data teams for your product areas
- Work with cross-functional teams and various stakeholders, including engineering, architecture, operations, product, marketing, partnerships, and customer success
- Collaborate with technical product analysts to support engineering teams through the delivery lifecycle
- Understand the implications of AI products to the healthcare industry, and be able to tell the story of how an individual receiving care maps to the problem you are solving
Requirements:
- 3+ years of technical product management with demonstrated ability to define product scope and deliver alongside technical teams
- Strong understanding of and experience with Data Science, ML, GenAI, and Data Analytics concepts and other data/product tools such as SQL, Python, R, Spark, AWS, Azure, and Snowflake
- An ability to listen to diverse audiences, identify requirements, gaps and barriers, and translate needs into AI and analytics solutions
- Understanding and experience with machine learning, data engineering, and software engineering
- Technical depth that enables you to drive discussions about design of AI solutions (including GenAI), machine learning models, ETLs, AI infrastructure
- Possess strong communication skills, including experience being an active and expert listener, with clear verbal communication as well as explicit and mindful written communication skills
- Well-versed in Agile frameworks and product tools such as Jira and Confluence
- Experience guiding teams through the AI lifecycle, including collecting and collating use cases and managing intake processes for new AI use cases
- Open to candidates with either B2B or B2C experience and outside the healthcare industry; critical to success in this role is being intellectually curious, a self-starter, and experience building AI products