
201 - 500 employees
⚕️ Healthcare Insurance
☁️ SaaS
🤝 B2B
💰 $100M Series C on 2021-03
Healthcare Insurance • SaaS • B2B
Rightway is a healthcare company focused on providing care navigation and pharmacy benefits management solutions. It specializes in helping employers and health systems lower healthcare costs and improve outcomes through personalized, proactive clinical support and transparent pharmacy benefits management. Rightway offers a human-first approach, providing real-time, one-on-one support to members to help them make better healthcare decisions and navigate the complexities of healthcare systems. The company aims to reduce healthcare costs while improving employee satisfaction with healthcare services.
🕒 February 12
🗽 New York – Remote
💵 $140k / year
⏰ Full Time
🟡 Mid-level
🟠 Senior
📊 Analytics Engineer
🦅 H1B Visa Sponsor
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201 - 500 employees
⚕️ Healthcare Insurance
☁️ SaaS
🤝 B2B
💰 $100M Series C on 2021-03
Healthcare Insurance • SaaS • B2B
Rightway is a healthcare company focused on providing care navigation and pharmacy benefits management solutions. It specializes in helping employers and health systems lower healthcare costs and improve outcomes through personalized, proactive clinical support and transparent pharmacy benefits management. Rightway offers a human-first approach, providing real-time, one-on-one support to members to help them make better healthcare decisions and navigate the complexities of healthcare systems. The company aims to reduce healthcare costs while improving employee satisfaction with healthcare services.
• Apply hands on analytics and data expertise to solve complex, fast moving financial and operational problems using PBM data. • Design, develop and maintain scalable, analytics ready data models (primarily in dbt) that power a PBM financial risk engine, leveraging claims, eligibility, pricing, rebates, guarantees and contract data in our Unified Data Warehouse (UDW). • Translate complex PBM contract and pricing structures (e.g plan paid vs. member paid, rebates, guarantees, caps, fees, exclusions) into transparent, auditable data models that enable financial analysis and risk assessment. • Partner closely with underwriting, finance, client success and PBM operations teams to understand financial assumptions, risk drivers and reporting requirements and convert them into reliable metrics and models. • Build curated financial and risk data marts and semantic layers that enable self service analysis for forecasting, scenario modeling and executive reporting among other things. • Own core financial KPIs and risk metrics E2E from raw claims and contract inputs through production grade models, ensuring consistency and traceability. • Implement automated data quality checks, reconciliations and controls to validate financial outputs and ensure alignment with source systems and contractual logic. • Continuously optimize data models and warehouse performance to support large scale claims volumes and time-sensitive financial analysis. • Contribute to data governance by establishing modeling standards, documentation and guardrails that support auditability, explainability and long term maintainability. • Communicate complex financial insights clearly through data memos, documentation and presentations for both technical and non technical stakeholders. • Explore advanced analytics and predictive modeling use cases (e.g utilization forecasting, trend analysis, risk stratification, margin sensitivity) to enhance financial planning and decision making. Experience operationalizing ML models is a plus.
• Expert level proficiency in SQL and statistical programming (Python, R). • 3 to 4 years working experience with data modeling, dbt and analytics engineering best practices (testing, documentation, incremental models, semantic layers). • Experience in cloud platforms (preferably in AWS) and hands-on experience in cloud data warehouses (Redshift or Snowflake). • Business acumen with exposure to PBM, healthcare finance, underwriting or actuarial concepts. • Experience modeling large scale claims data and translating contractual or financial rules into clear, testable data logic. • Strong analytical and problem-solving skills. • Ability to understand, tackle, and solve problems from both technical and business perspectives. • Comfortable partnering closely with finance, underwriting and operations stakeholders to align data models with real world financial decisions. • High attention to detail and a bias toward accuracy, transparency and explainability in financial reporting.
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