Product Manager, Data Platform

The Product Manager for the Data Platform at Cohere Health is responsible for overseeing the data store strategy, ensuring data quality across internal teams and external partners, defining patient event data requirements, and collaborating with various stakeholders to support data-driven decision-making. This role is pivotal in maintaining the integrity of our data processes and partnering with technology teams to ensure schema compatibility across data ingestion and processing pipelines.

To apply for the Product Manager, Data Platform role at Cohere Health, candidates should have a minimum of 3 years of experience in product management within the healthcare domain, with at least 2 years focused specifically on data platforms and analytics. A strong understanding of data concepts, cloud environments, and data governance is also necessary, along with the ability to translate complex technical ideas into actionable business strategies.

Success as a Product Manager at Cohere Health requires strong analytical skills, the ability to collaborate effectively with engineering and analytics teams, proficiency in Agile methodologies, and familiarity with project management tools like JIRA and Trello. Additionally, candidates should be problem solvers with a meticulous approach to data quality and governance, as well as a solid understanding of BI platforms and cloud technologies.

Cohere Health is committed to building a diverse and inclusive workplace, which extends to the Product Management team. The company believes that diverse perspectives lead to better decision-making and more innovative solutions. Cohere promotes an environment of mutual respect, providing equal employment opportunities and fostering a supportive culture that values each team member's contributions.

The salary range for the Product Manager, Data Platform at Cohere Health is between $125,000 and $140,000 annually. This is part of a comprehensive benefits package that includes health insurance and a 401k plan. Individual pay decisions are influenced by factors such as experience, qualifications, and internal alignment within the company.

When responding to this question, showcase specific experiences you've had with healthcare data. Discuss your familiarity with healthcare data types, analytics use cases, and how you have previously ensured data quality. Highlight key projects or collaborations you've had that tie directly back to product management in this domain.

To answer this, explain your method for prioritization, perhaps mentioning frameworks like the MoSCoW method or how you analyze impact versus effort. Emphasize your communication skills, how you engage with stakeholders to understand priorities, and how you balance urgent tasks against long-term goals.

Describe your hands-on experience with Agile methodologies such as Scrum or Kanban. Talk about your roles in sprint planning, daily stand-ups, retrospectives, and how you've adapted Agile practices to suit the needs of your cross-functional teams.

Discuss your approach to data quality management, including the strategies you implement to maintain high standards. Talk about the importance of documentation, collaborating with data governance teams, and employing best practices for data stewardship.

Select a specific product launch to discuss, detailing your role in the launch process. Explain the planning phase, the cross-team collaboration, challenges overcome, and the measurable success metrics achieved that underpinned the launch's effectiveness.

Mention specific project management tools such as JIRA or Trello and discuss why you favor them for data project management. Talk about how these tools contribute to tracking progress, managing scope, and especially how they enhance collaboration among different teams.

In your response, outline your commitment to continuous learning. Mention any industry publications you subscribe to, professional networks, online courses, or conferences you attend to stay abreast of innovations and trends related to data platforms and healthcare analytics.

Discuss your familiarity with cloud platforms such as AWS, Azure, or Google Cloud, highlighting specific projects where you utilized these technologies. Emphasize your understanding of cloud storage solutions, cost management, and security aspects specific to data management in the cloud.

Share relevant projects involving AI or machine learning, even if your direct role was not as a data scientist. Focus on your collaboration with data science teams, how you leveraged AI insights to inform product development, and the outcomes related to the engagement.

Talk about your strategies for engaging stakeholders, emphasizing the importance of open communication and empathy. Discuss techniques such as workshops, interviews, or feedback surveys that you utilize to gather insights that inform product development.