Data Scientist

Role Overview

As a Data Scientist at Metriport, you’ll own clinical intelligence across the company’s stack—turning large volumes of clinical records into predictions, insights, and automated decisions. The role blends ML, analytics, and building the underlying data foundation in a fast-moving, autonomy-driven team.

Responsibilities

• Apply AI/ML to clinical data to:
  • predict patient outcomes
  • identify gaps in care
  • detect/surface anomalies across data warehouse data
• Normalize clinical data at scale using NLP/LLMs or rule-based systems to transform messy unstructured records into structured, searchable, trustworthy data
• Own analytics and data quality when it matters
  • take shared responsibility for the analytics stack and reliable metrics
  • provide accurate reporting for customers and internal stakeholders
• Productize intelligence by shipping data-science-powered features that are used by customers (not only experiments)
• Build the data foundation alongside engineering, contributing to:
  • data modeling
  • warehouse design
  • data tooling and infrastructure (e.g., dbt, data warehouses, PostHog)
• Team alignment via a daily 30-minute remote standup at 7:30 AM PST (Mon–Fri)

Requirements

• 4+ years in a data science role (ideally in a high-growth startup where you wore multiple hats)
• SQL mastery: can write complex, performant queries
• Practical ML/statistics experience with building and deploying models such as:
  • classification, regression, clustering
  • NLP
• Strong Python proficiency (e.g., pandas, scikit-learn) and experience integrating with LLM APIs/frameworks
• Strong analytical skills (comfort working with messy data and root-cause analysis)

Nice-to-haves

• TypeScript proficiency (stack is TypeScript-heavy)

Location / Work Setup

• Based in California, United States (SF office referenced); daily standup is remote at 7:30 AM PST.