Staff Data Scientist | Analytics

Machinify is a leading healthcare intelligence company with expertise across the payment continuum, delivering unmatched value, transparency, and efficiency to health plan clients across the country. Deployed by over 85 health plans, including many of the top 20, and representing more than 270 million lives, Machinify brings together a fully configurable and content-rich, AI-powered platform along with best-in-class expertise. We’re constantly reimagining what’s possible in our industry, creating disruptively simple, powerfully clear ways to maximize financial outcomes and drive down healthcare costs. What You'll Do Independently partner with business stakeholders to understand complex operational challenges, build domain context, and frame analytical approaches — without predefined solutions or heavy direction Perform deep exploratory data analysis across payment operations, chart review workflows, and customer performance metrics to diagnose root causes and identify optimization opportunities Build and maintain dashboards and reporting infrastructure that give leaders real-time visibility into operational and financial performance Conduct business reviews including month-to-month bridges, waterfall analyses, and price-volume-mix decompositions to explain performance variance Use LLMs and AI-assisted tools (e.g., Claude, GPT) for data exploration, pattern identification, and accelerating analytical workflows Translate ambiguous business questions into structured analytical approaches with clear, actionable recommendations Work with both models and querying to understand problems — diagnosing first, then standardizing and building scalable solutions Partner cross-functionally with Product, Data Science, Engineering, and Operations teams to deliver analytics-ready solutions Build foundational data assets — base data sets, aggregates, and pipelines — required for robust reporting and insight generation What You Bring 4-6 years of experience in product analytics OR a high-level business analytics role (quantifying product/business impact, translating data/insights/KPI into business decisions, showing impact using data and analysis, translating complex data analysis into stories to influence business decisions, etc.) Strong proficiency in SQL and Python for data manipulation, analysis, and visualization Demonstrated ability to independently diagnose complex business problems through exploratory data analysis — comfortable working without predefined solutions Experience with BI/visualization tools (e.g., Power BI, Tableau, Looker) and building dashboards for business stakeholders Familiarity with LLMs and AI tools for data analysis — comfortable using AI-assisted workflows to accelerate insight generation and excited to push the boundaries of what's possible Degree in a quantitative field (e.g., Economics, Statistics, Operations Research, Data Science, Engineering, or related discipline) Strong communication and storytelling skills — ability to work directly with senior stakeholders and present complex findings clearly to both technical and non-technical audiences Experience working with large-scale data warehouses (Databricks, Snowflake, BigQuery, or similar) Consulting mindset: ability to quickly build business context in unfamiliar domains, structure ambiguous problems, and deliver actionable recommendations Curiosity, growth mindset, and excitement about learning new areas — including healthcare, LLMs, and GenAI Comfort operating in a fast-paced, ambiguous environment and balancing short-term deliverables with longer-term strategic work Nice-to-Haves Background in management consulting or strategic advisory (McKinsey, BCG, Bain, Deloitte, or similar) Economics background with understanding of causal reasoning and business impact measurement Experience in healthcare, payment integrity, or health insurance operations (or strong aptitude for quickly learning complex regulated domains) Experience with ... (truncated, view full listing at source)