Senior Product Manager
Medeloop
full-time
Posted on:
Location Type: Remote
Location: United States
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Job Level
About the role
- Partner daily with ML engineers and AI research teams to translate model capabilities into user-facing analytics features that are reliable, interpretable, and clinically meaningful.
- Rapidly prototype features and workflows using AI-assisted development tools to validate ideas, test hypotheses, and de-risk engineering investment before committing to full builds.
- Design and own the benchmarking and evaluation strategy for AI-driven analytics—define quality standards, build evaluation frameworks, and ensure our platform meets rigorous accuracy, reliability, and performance thresholds.
- Work directly with large-scale healthcare data (claims, EHR) using SQL and Python to inform product decisions, validate analytical outputs, and develop intuition for data quality issues.
- Define multi-layered success metrics that connect model-level performance (precision, recall, F1) to product-level outcomes (user adoption, task completion) and business-level impact (research acceleration, customer expansion).
- Lead cross-functional execution across engineering, data science, design, and clinical/research stakeholders, ensuring alignment and shipping velocity in a fast-moving environment.
Requirements
- 3–5 years of product management experience on technical, data-intensive, or ML-powered products.
- Hands-on proficiency with SQL and Python for data exploration, analysis, and hypothesis validation—not just reading dashboards, but writing queries and scripts yourself.
- Experience designing evaluation frameworks, benchmarks, or quality metrics for AI/ML systems. You understand what it means to define “good” for a probabilistic system.
- Demonstrated ability to rapidly prototype and ship 0→1 products. You default to building something to learn rather than speccing in the abstract.
- Strong understanding of ML/AI concepts—you can partner deeply with data scientists and ML engineers, ask the right questions about model behavior, and reason about tradeoffs, without needing to train models yourself.
- Comfort with ambiguity and non-deterministic product behavior. You’ve defined success for systems where the same input doesn’t always produce the same.
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
SQLPythonAI-assisted development toolsevaluation frameworksbenchmarksquality metricsdata explorationdata analysisprototypingML/AI concepts
Soft Skills
cross-functional executioncommunicationproblem-solvingadaptabilitycollaborationleadershipcritical thinkinguser-centric mindsetambiguity managementstakeholder alignment