Senior Data Scientist

Clover Health

1d•Remote

About The Position

At Counterpart Health, we are transforming healthcare and improving patient care with our innovative tool, Counterpart Assistant. By supporting Primary Care Physicians (PCPs), we are able to deliver improved outcomes to our patients at a lower cost through early diagnosis and longitudinal care management of chronic conditions. The Data Science team is responsible for leveraging our most valuable asset—our data—to generate meaningful value for our members. From building models that assist physicians in treating conditions to identifying members in need of specialized care, Data Science at Clover develops data products and insights that are central to our mission and differentiation as a company. Our impact is tremendous—as a Senior Data Scientist, you’ll help build a revolutionary healthcare company by delivering data-driven solutions that directly improve patient outcomes.

Requirements

You have an advanced degree in a quantitative field (Master’s + 3-4 years of experience or Ph.D. + 2+ years of experience).
You have a strong foundation in probability, statistics, and machine learning tools, including SQL, Python, and relevant ML/statistical packages.
You have successfully used data science to drive enterprise value in a business function.
You are comfortable leading projects and have experience taking large-scale initiatives from concept to measurable business impact.
You improve the work of those around you through mentorship, code review, and leadership by example.
You can clearly communicate how your work contributes to business goals, ensuring alignment with top-level company objectives.

Responsibilities

Lead large-scale projects from ideation through enterprise impact.
Apply a broad problem-solving toolkit to develop both creative and practical solutions.
Evaluate trade-offs between out-of-the-box and customized solutions, optimizing for speed and effectiveness.
Implement scalable, bug-free, and well-tested solutions that reduce complexity rather than add to it.
Understand business challenges and deliver results that meaningfully solve key problems.
Proactively engage with stakeholders across all levels to align data science efforts with business needs.
Identify and mitigate risks early, preventing roadblocks that could arise later.
Serve as a trusted advisor and thought partner, ensuring projects are delivered on time and aligned with business objectives.
Mentor and collaborate with peers, improving team-wide problem-solving capabilities and technical execution.