Senior Applied Scientist, Decisioning

Pivotal Health•Los Angeles, CA

1d•Remote

About The Position

Pivotal Health is seeking a Senior Applied Scientist, Decisioning to enhance the systems responsible for making high-value decisions within core workflows. This role is ideal for individuals with a strong background in applied data science or optimization who are eager to work on production systems and drive measurable impact. The position involves operating at the intersection of data, experimentation, modeling, economics, and software. Potential areas of focus include the offer engine, feedback mechanisms for model and rule enhancements, configurable decision systems, experimentation on operational workflows, and other products where improved decision quality directly influences business outcomes. The company is particularly interested in candidates with experience in challenging decisioning problems within domains such as marketplaces, pricing and revenue optimization, lending and credit, ad tech, bidding systems, or similar fields where experimentation, optimization, and operational constraints are critical. This is a hands-on role focused on moving from analysis and modeling to production changes with tangible impact. The ideal candidate will be AI-first in their approach, actively using AI for exploration, analysis, iteration, experimentation, and engineering support, and will contribute to fostering an AI-native work culture.

Requirements

Excitement for high-stakes decisioning problems that integrate data, uncertainty, incentives, and operational constraints.
Strong applied data science instincts with a desire to ship work.
Comfort moving between modeling, experimentation, analysis, and product or engineering collaboration.
Ability to reason clearly about metrics, tradeoffs, and second-order effects.
Pragmatic approach to problem-solving, selecting the appropriate level of sophistication.
Proficiency as an AI power user, actively using AI in daily work with sound judgment.
Adaptability to fast-moving environments with undefined paths, driving impact through good judgment and speed.

Nice To Haves

Experience in pricing, revenue optimization, marketplace ranking, matching, bidding, lending, credit, underwriting, or ad tech systems.
Experience designing and interpreting experiments in production environments.
Experience with optimization, decisioning, forecasting, or applied statistics in high-leverage product systems.
Experience partnering closely with engineers to productionize models, logic, or recommendations.
Experience with Python and backend-adjacent technical workflows.
Experience transforming complex business problems into measurable systems with clear operating tradeoffs.
Experience in healthcare or other operationally complex industries.

Responsibilities

Improve decisioning systems impacting pricing, offer behavior, workflow routing, and other economically significant product outcomes.
Design and execute experiments to evaluate the performance improvements of product, rules, prompt, or model changes.
Develop models, heuristics, optimization logic, or evaluation frameworks to enhance real-world outcomes under operational constraints.
Translate business objectives into measurable decisioning systems that clearly define tradeoffs and success criteria.
Collaborate closely with engineers to productionize new logic, moving beyond notebooks or offline recommendations.
Help design feedback loops that connect model and workflow behavior to product and business outcomes.
Contribute to configurable rules systems and other controls to facilitate easier management and improvement of decisioning over time.
Utilize AI as a force multiplier in personal workflows and help the team increase speed through strong AI-native habits.
Balance rigor and speed in an environment that prioritizes shipping and continuous iteration.