Staff Data Scientist

Pivotal Health•Los Angeles, CA

1d•$200,000 - $230,000•Remote

About The Position

Pivotal Health is seeking a Staff Data Scientist, Decisioning to enhance 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. Responsibilities may include working on offer engines, feedback loops for model and rule improvements, configurable decision systems, and experimenting with operational workflows. The company is particularly interested in candidates with experience in complex decisioning problems within domains such as marketplaces, pricing and revenue optimization, lending and credit, ad tech, and bidding systems. This is a hands-on role focused on productionizing solutions rather than pure research, emphasizing AI-first workflows for exploration, analysis, iteration, experimentation, and engineering support. The goal is to build a strong AI-native way of working and achieve measurable business outcomes.

Requirements

Excited by high-stakes decisioning problems that combine data, uncertainty, incentives, and operational constraints.
Strong applied data science instincts with a desire for work to ship.
Comfortable moving between modeling, experimentation, analysis, and product or engineering collaboration.
Ability to reason clearly about metrics, tradeoffs, and second-order effects.
Pragmatic approach, choosing the right level of sophistication for the problem.
AI power user, actively using AI in day-to-day work with good judgment.
Ability to operate in fast-moving environments where the path is not perfectly defined and impact comes from good judgment plus 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 tightly with engineers to productionize models, logic, or recommendations.
Experience with Python and backend-adjacent technical workflows.
Experience turning messy business problems into measurable systems with clear operating tradeoffs.
Experience in healthcare or other operationally complex industries.

Responsibilities

Improve decisioning systems that affect pricing, offer behavior, workflow routing, and other economically meaningful product outcomes.
Design and run experiments that help us understand whether product, rules, prompt, or model changes are actually improving performance.
Build models, heuristics, optimization logic, or evaluation frameworks that improve real-world outcomes under operational constraints.
Help translate business objectives into measurable decisioning systems with clear tradeoffs and success criteria.
Work closely with engineers to productionize new logic rather than stopping at notebooks or offline recommendations.
Help design feedback loops that connect model and workflow behavior back to product and business outcomes.
Contribute to configurable rules systems and other controls that make decisioning easier to manage and improve over time.
Use AI as a force multiplier in your own workflow and help the team move faster by bringing strong AI-native habits.
Balance rigor and speed in an environment where shipping matters and iteration is constant.