Product Manager (Technical)
LeanTaaS uses data science and machine learning to make hospitals efficient. Our products leverage advanced algorithms to maximize resource utilization and improve operational efficiency. More than 45 healthcare providers, including some of the nation’s largest such as Memorial Sloan Kettering, MD Anderson, Stanford Health Care, University of Colorado Health, NewYork-Presbyterian & more rely on LeanTaaS to lower patient waiting times and improve patient access. To date, the company has helped more than one million cancer patients get better treatments. We are solving the US healthcare cost problem through getting hospitals to adopt predictive analytics, and smart mobile and web technologies.
Our leadership team includes ex-Google / McKinsey veterans with decades of experience building successful technology companies. We are backed by some of the most prominent investors in healthcare.
- Own product vision, strategy, and execution for operational improvement software products using data analysis, operations research, and machine learning.
- Analyze customer operational data using tools such as Tableau, R, and Python and identify operational issues and inefficiencies such as underutilization or overutilization of expensive assets, poor distribution of asset allocation, etc.
- Develop analytics, mathematical models and decision support tools to solve operational problems using Tableau, R and Python.
- Collaborate with peer product managers, data scientists, and engineers to review and refine the mathematical models and analytics.
- Run simulations on the mathematical models and analytics using various inputs and scenarios to verify the efficacy, sanity, and performance; and develop criteria and mechanisms to select the most optimal models and analytics for production.
- Develop technical specifications to add the most optimal models and analytics to the product.
- Work with data scientists and engineers to implement the models and analytics inside the software product.
- Monitor progress of the development of those models and analytics on a daily basis, answer questions as needed, and ensure that the projects are completed on time.
- Validate the models by developing tools in Python and R to check model inputs and outputs via product APIs and verify the assumptions, calculations, and efficacy performance of the models and analytics.
- Work with operational leaders at customer healthcare organizations to deploy the mathematical models, decision support and analytics software products at their organizations.
- Monitor the models and analytics on a daily basis by developing tools to validate and correct the data received, and tools to validate the outputs and expected behavior.
- Work with customer operational leaders, data scientists and engineers to resolve issues with the models and analytics in a timely manner and ensure product success.
- Bachelor’s Degree in mathematics / statistics, engineering / physics, or data science / operations research.
- Experience working with enterprise SAAS (software as a service) products
- Experience working with REST APIs and web services
- Experience working with SQL / Data pipelines
- Strong experience writing technical specs (JIRA or similar)
- Experience with data analysis using sophisticated data analysis tools such as Tableau, SPSS, etc.
- Experience with programming languages such as R, Python, Java, C or C++.
- Excellent analytical, critical thinking, and problem-solving skills.
- Excellent written and verbal communication skills and experience working with cross-functional agile (scrum/kanban) teams.
- Excellent organizational skills.
- Excellent leadership and people skills.
- 2+ years of working experience in product management or development