Staff Data Scientist, Growth

Pearl Health

2d•$160,000 - $200,000

About The Position

We are seeking a sales-oriented Staff Data Scientist – think Sales Engineer, but for Data Science – who can lead complex, cross-functional initiatives and communicate deep technical nuance to sophisticated, but non-technical audiences. You will function as a strategic bridge between our Data Science and Growth teams, not only giving voice to analyses but proactively identifying and mitigating project risks weeks in advance. You should be an effective coordinator across verticals and a strategic thinker with a deep understanding of current business needs and industry trends. The role will leverage and extend our analytic platform to design an ecosystem of explanatory tooling that will provide an explicability layer for our underwriting models. You will align these interpretability projects with an evolving and highly seasonal go-to-market motion, utilizing GenAI as a strategic thought partner to accelerate system design. Additionally, you will influence the strategy and technical choices that impact the company’s financial offer, sales motion and risk management framework, by providing high-level feedback to colleagues on how we can further differentiate and elevate Pearl’s offerings in a competitive sales environment while intelligently managing Pearl’s financial exposure. Pearl Health is dedicated to empowering primary care providers, health systems, and physician-led networks to succeed in the shift to value-based care. Our platform delivers the technology, financial tools, and expert services that enable practices to provide more proactive, effective care to their Medicare patients, ultimately lowering costs and improving health outcomes. Founded in 2020, we are a team of healthcare and technology innovators backed by premier investors like Andreessen Horowitz, Viking Global Investors, and AlleyCorp. We partner with thousands of providers across 44 states to build a more sustainable future for American healthcare.

Requirements

8+ years of experience in performing results-driven quantitative analysis in a healthcare management or professional consulting environment.
A degree in statistics, applied math, computer science, engineering or a related field (e.g., healthcare policy) is strongly preferred.
SQL expertise and strong foundation in at least one of the main data science programming languages (Python, R, Julia, Scala, Matlab). Python is our current primary language and is preferred.
Eloquent communicator who can communicate deep technical nuance to internal teams while up-leveling understanding for lay audiences.
Relish synthesizing the complexity of the healthcare/financial ecosystem into actionable insights that provide value to providers.
A proven mentor who fosters a culture of technical rigor and mentors more junior team members.
A proven ability to apply research and analytic models to inform growth operations, with a high "hit rate" that indicates accurate intuition for promising nascent research.

Responsibilities

Engaging with sales leads as a “human explicability layer,” up-leveling understanding for non-technical audiences to ensure that complex underwriting results are communicated clearly to drive sales. While you will have direct contact with prospects, you will also identify opportunities to automate explicability through robust technical systems. Crucially, you will use points of friction or resonance observed in the field to inspire the roadmap for our core ML team, ensuring our models and features evolve in direct response to market needs and stakeholder feedback.
Leading complex and dynamic collaborations between the Data Science and Growth teams. This requires not just organizing resources, but proactively identifying and mitigating risks to ensure SLAs are met or exceeded.
Helping us refine the competitiveness of our value-based care contracts. You will anticipate stakeholder needs and provide strategic guidance on which aspects of our sales offerings are compelling, proactively proposing new work based on these business insights.
Ensuring quality and availability of various data sources. You will set standards for code quality and reproducibility regarding lead information, sales touchpoints, and financial analyses.
Leveraging a deep understanding of ML concepts (e.g., using SHAP or feature importance but also less formal quantitative instinct) to consult on the application of payment models. You will develop a deep orientation to the core team’s outputs, ensuring our financial logic is both accurate and explainable for provider-facing scenarios.
Designing and engineering analytics tooling to stress-test our underwriting outputs. You will use your technical expertise to contemplate where models may be weak and investigate corner cases, ensuring our growth motion is supported by high-fidelity, defensible data in the upcoming season.
Deepening knowledge of healthcare models. Developing a deep understanding of industry trends (e.g., LEAD, REACH, MSSP, Medicare Advantage) and data heterogeneity to align with Pearl's strategic roadmap.
Evaluating vendors and technologies. Participating in evaluations for core technologies to help us better understand our customers and the market.