Job description

Company Overview: Blink Health is the fastest growing healthcare technology company that builds products to make prescriptions accessible and affordable to everybody. Our two primary products – BlinkRx and Quick Save – remove traditional roadblocks within the current prescription supply chain, resulting in better access to critical medications and improved health outcomes for patients. BlinkRx is the world’s first pharma-to-patient cloud that offers a digital concierge service for patients who are prescribed branded medications. Patients benefit from transparent low prices, free home delivery, and world-class support on this first-of-its-kind centralized platform. With BlinkRx, never again will a patient show up at the pharmacy only to discover that they can’t afford their medication, their doctor needs to fill out a form for them, or the pharmacy doesn’t have the medication in stock. We are a highly collaborative team of builders and operators who invent new ways of working in an industry that historically has resisted innovation. Join us! About the Role BlinkRx is looking for a Principal Data Scientist to join a small, elite team of senior data practitioners operating at the very highest levels of the organization. This is an individual contributor role - not a strategic advisory seat - where you will roll up your sleeves and solve some of the most consequential problems in healthcare commerce. You will sit at the intersection of data science, data engineering, and advanced analytics - building the algorithms, multidimensional models, and analytical frameworks that directly improve business outcomes and patient care. Critically, you will also influence your work: translating complex, multi-dimensional findings into clear narratives that business stakeholders can act on. What You'll Do Develop a deep understanding of customer and patient behavior to identify unmet needs, sources of product friction, and opportunities to improve the customer experience. Partner closely with Product, Engineering, and Operations to translate customer insights into product strategy, roadmap prioritization, and measurable outcomes. Define product success metrics and build measurement frameworks that evaluate customer engagement, adoption, retention, and business impact. Design and build AI-powered analytical tools and agentic workflows that improve productivity, automate repetitive analyses, and enable more effective product decision-making. Apply statistical modeling, predictive analytics, and exploratory analysis to better understand customer behavior and inform product strategy. Build analytical tools and scalable data models that enable product teams to make faster, data-informed decisions. Communicate clear, actionable insights and recommendations to executives and cross-functional stakeholders, influencing product strategy through data. Mentor other data scientists and help establish best practices in experimentation, measurement, and analytical rigor. What You'll Need 10+ years of experience in Data Science, Product Analytics, Statistics, Economics, or another quantitative discipline. Demonstrated success translating ambiguous business problems into actionable analytical solutions. Deep expertise in statistical analysis, experimentation, causal inference, and predictive modeling. Experience applying modern AI technologies, including large language models (LLMs) and agentic workflows, to solve business problems and improve analytical productivity. Expert proficiency in SQL and experience working with large, complex datasets. Strong programming skills in Python, R, or another analytical programming language. Experience partnering closely with Product and Engineering teams to guide product strategy through data. Experience with BI and visualization tools such as Tableau, Databricks or similar platforms. Excellent communication skills with the ability to influence technical and non-technical stakeholders, including executive leadership. A pragmatic, business-oriented approach to solving complex problems with data. A growth mindset, intellectual curiosity, and a passion for improving products through evidence-based decision making. Nice to Have Experience building AI-powered applications, evaluation harnesses, and agentic workflows for production use. Hands-on experience building and deploying production-grade machine learning and analytics solutions using Databricks (Delta Lake, MLflow, Feature Store, Model Serving, or related capabilities). Experience working in healthcare, digital health, eCommerce, or consumer technology. Experience mentoring data scientists and raising the bar for analytical excellence. Why Join Us: It is rare to have a company that both deeply impacts its customers and is able to provide its services across a massive population. At Blink, we have a huge impact on people when they are most vulnerable: at the intersection of their healthcare and finances. We are also the fastest growing healthcare company in the country and are driving that impact across millions of new patients every year. Our business model not only helps people, but drives economics that allow us to build a generational company. We are a relentlessly learning, constantly curious, and aggressively collaborative cross-functional team dedicated to inventing new ways to improve the lives of our customers. We are an equal opportunity employer and value diversity of all kinds. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. Applicants who provide their phone number and consent to receive text messages may receive SMS or MMS updates from Blink Health regarding their application.

Requirements

Must-haves

Develop a deep understanding of customer and patient behavior to identify unmet needs, sources of product friction, and opportunities to improve the customer experience.
Partner closely with Product, Engineering, and Operations to translate customer insights into product strategy, roadmap prioritization, and measurable outcomes.
Define product success metrics and build measurement frameworks that evaluate customer engagement, adoption, retention, and business impact.
Design and build AI-powered analytical tools and agentic workflows that improve productivity, automate repetitive analyses, and enable more effective product decision-making.
Apply statistical modeling, predictive analytics, and exploratory analysis to better understand customer behavior and inform product strategy.
Build analytical tools and scalable data models that enable product teams to make faster, data-informed decisions.
Communicate clear, actionable insights and recommendations to executives and cross-functional stakeholders, influencing product strategy through data.
Mentor other data scientists and help establish best practices in experimentation, measurement, and analytical rigor.
What You'll Need
10+ years of experience in Data Science, Product Analytics, Statistics, Economics, or another quantitative discipline.
Demonstrated success translating ambiguous business problems into actionable analytical solutions.
Deep expertise in statistical analysis, experimentation, causal inference, and predictive modeling.
Experience applying modern AI technologies, including large language models (LLMs) and agentic workflows, to solve business problems and improve analytical productivity.
Expert proficiency in SQL and experience working with large, complex datasets.
Strong programming skills in Python, R, or another analytical programming language.
Experience partnering closely with Product and Engineering teams to guide product strategy through data.
Experience with BI and visualization tools such as Tableau, Databricks or similar platforms.
Excellent communication skills with the ability to influence technical and non-technical stakeholders, including executive leadership.
A pragmatic, business-oriented approach to solving complex problems with data.
A growth mindset, intellectual curiosity, and a passion for improving products through evidence-based decision making.

Nice-to-haves

Experience building AI-powered applications, evaluation harnesses, and agentic workflows for production use.
Hands-on experience building and deploying production-grade machine learning and analytics solutions using Databricks (Delta Lake, MLflow, Feature Store, Model Serving, or related capabilities).
Experience working in healthcare, digital health, eCommerce, or consumer technology.
Experience mentoring data scientists and raising the bar for analytical excellence.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aisqlpythonmachine learning

Platform: greenhouse
Effort: quick