Senior Product Manager

Medeloop is seeking a Product Manager to drive the vision for our Analytics platform—the core surface through which researchers, clinicians, and biopharma teams interact with AI-generated insights at scale. In this role, you will define what we build, how we measure quality, and how our analytics capabilities evolve to meet the needs of healthcare and life sciences.

You will work hand-in-hand with Medeloop’s ML and AI research teams, translating model capabilities into features that users trust and rely on. This is a hands-on, builder-oriented role: you’ll prototype rapidly using AI-assisted development tools, work directly with healthcare data in SQL and Python, and lead the design of benchmarking and evaluation frameworks that define what “good” looks like for our AI-driven analytics.

The ideal candidate combines product intuition with genuine technical depth—someone who can move fluidly between writing a product spec, querying a claims dataset, prototyping a feature, and designing an eval to measure whether the AI got it right.

Role & Responsibilities

• 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.

• 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 

• Background in healthcare data, clinical analytics, health informatics, or real-world evidence (claims/EHR data).
• Experience with distributed data systems such as PySpark or similar large-scale data processing frameworks.
• Prior work in benchmarking methodology, model evaluation pipelines, or AI quality assurance for production systems.