Staff Data Scientist, AI-Driven Decisioning

Pivotal Health; San Francisco, Northern (CA, KY); Hybrid; USD 180,000 - 240,000; Full time

Benefits offered by this job

Health benefits

Equity/stock options

401(k) retirement plan

Flexible time off

Company-wide events

Job summary

Pivotal Health is hiring a Staff Data Scientist, Decisioning to improve core decisioning systems that drive pricing and workflow routing. You’ll work at the intersection of data, experimentation, modeling, economics, and software.

This is not just offline analysis—expect to ship production changes with measurable impact, partnering with engineers to operationalize new logic and design decision loops that move business metrics.

Qualifications

• Strong applied data science instincts and ability to ship.
• Experience designing and interpreting experiments in production environments.
• Proficiency in Python and backend-adjacent workflows.
• Familiarity with decisioning systems, pricing, and optimization is a plus.
• Experience collaborating with engineers to productionize models and logic.

Responsibilities

• Improve decisioning systems affecting pricing and workflow routing.
• Design and run experiments to test product, rules, and model changes.
• Build models, heuristics, optimization logic, or evaluation frameworks.
• Translate business objectives into measurable decisioning systems with clear tradeoffs.
• Collaborate with engineers to productionize new logic beyond notebooks.
• Design feedback loops linking model behavior to product and business outcomes.
• Contribute to configurable rules systems and decisioning controls.
• Use AI to accelerate exploration, analysis, and engineering support.

Skills

Applied data science instincts

Experimentation design

Python

Backend workflows

Decisioning systems

Tools

ML tooling

Job description

Pivotal Health is hiring a Staff Data Scientist, Decisioning to improve core decisioning systems that drive pricing and workflow routing. You’ll work at the intersection of data, experimentation, modeling, economics, and software.

This is not just offline analysis—expect to ship production changes with measurable impact, partnering with engineers to operationalize new logic and design decision loops that move business metrics.