Staff Data Scientist

Pivotal Health; Santa Monica (CA); On-site; USD 150,000 - 210,000; Full time

Job summary

Pivotal Health is hiring a Staff Data Scientist, Decisioning to improve systems that determine how the company makes high-value decisions in core workflows.

You will work at the intersection of data, experimentation, modeling, economics, and software, applying AI-first approaches to production-ready decisioning across offer engines and operational workflows. This role emphasizes rapid, measurable impact in a fast-paced environment.

Qualifications

• Strong applied data science or optimization background required.
• Experience moving from analysis to production changes with measurable impact.
• AI-first workflow experience and curiosity to use AI for exploration and iteration.
• Ability to translate business objectives into measurable decisioning systems.

Responsibilities

• Improve decisioning systems that affect pricing and workflow outcomes.
• Design and run experiments to evaluate changes.
• Build models, heuristics, or evaluation frameworks under constraints.
• Translate business objectives into measurable decisioning systems with clear tradeoffs.
• Work with engineers to productionize new logic.

Skills

Applied data science

Optimization

Experimentation

Productionization

AI-first workflow

Decisioning

Job description

About Pivotal Health

Pivotal Health is the leading technology platform that helps healthcare providers get paid fairly in an increasingly complex reimbursement landscape.

Today, many providers face persistent underpayment from health insurance companies, despite delivering high-quality care. While processes like IDR (Independent Dispute Resolution) were designed to promote fairness, they’re often administrative-heavy, time-consistent, and difficult to navigate without the right tools.

Pivotal Health combines software, data, and service into a seamlessly integrated, AI-driven platform that simplifies these complex reimbursement workflows. We help providers efficiently dispute underpaid claims, reduce administrative burden, and recover the reimbursement they’re entitled to; without adding more work to already stretched teams.

Our full-service IDR solution is just the starting point. We’re building solutions that enable providers to operate with clarity, control, and confidence across the reimbursement journey.

About the Role

We’re hiring a Staff Data Scientist, Decisioning to improve the systems that determine how Pivotal makes high-value decisions in core workflows.

This role is for someone with a strong applied data science or optimization background who wants to work on real production systems, not just offline analysis. You’ll operate at the intersection of data, experimentation, modeling, economics, and software. The work may span areas like the offer engine, feedback loops for model and rule improvements, configurable decision systems, experimentation on operational workflows, and other products where better decision quality directly improves business outcomes.

We’re especially interested in candidates who have worked on hard decisioning problems in environments like marketplaces, pricing and revenue optimization, lending and credit, ad tech, bidding systems, or other domains where experimentation, optimization, and operating constraints all matter at once.

This is not a research-only role. We want someone who can think deeply, work rigorously, and still move quickly from analysis and modeling into production changes with measurable impact.

We also want someone who is AI-first in their own workflow. The right person will use AI actively for exploration, analysis, iteration, experimentation, and engineering support, and will help the team build a strong AI-native way of working.

What You’ll Do

• 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.

What Success Looks Like

In the first 6 to 12 months, strong outcomes in this role would include:

• meaningful improvements to the offer engine or related decision systems

• high-quality experiments that clarify which changes actually improve outcomes

• stronger feedback loops between model behavior, rule behavior, and business performance

• better visibility into tradeoffs across quality, economics, operational cost, and user outcomes

• becoming a trusted owner of an important decisioning surface

• helping raise the team’s bar on experimentation, analytical rigor, and evidence-based iteration