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Staff Data Scientist - Finance & Accounting

Headway
CompanyHeadway
CategoryData & Analytics
LocationNew York
RemoteOn-site (inferred)
EmploymentNot stated
LevelNot stated
SalaryUSD 212k–265k
Posted27 Mar 2026
Last verified11 Aug 2026
SourceEmployer ATS (ashby)
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Description
1 in 4 people in the US have a treatable mental health condition, but most providers don't accept insurance, making therapy too expensive for most people. Headway’s mission is to fix this by building a new mental healthcare system everyone can access. We started by solving the biggest barrier to care: insurance. The admin work - credentialing, claims, payment reconciliation - is a nightmare. We've automated that. But we're going further. Over 75,000 providers across all 50 states run their practice on our software, serving over 1 million patients. We are building the best tools for therapists to run their entire practice, reimagining the experience of finding a therapist, and investing in the platform foundations to enable this at scale. We aren't just a billing layer; we are becoming the platform where care actually happens. We're a Series D company with $325M+ in funding (a16z, Accel, Spark Capital, etc.), looking for exceptional people to help us achieve this mission. We want your time here to be the most meaningful experience of your career. Join us, and help change mental healthcare for the better. About the Role: As a Staff Data Scientist for Finance and Accounting, you will drive data insights strategy for Headway's financial ecosystem. Your mission is to provide a holistic understanding of our financial health and our revenue infrastructure.  You will report into the Data team and support Headway's Insurance Group, a mission critical pillar that ensures the systems behind our insurance platform reliably power patient, provider, and payer experiences. Accurate and complete financial visibility is a core part of our operations and essential to Headway's growth.  You will partner closely with both the Finance department (including Accounting, Strategic Finance, and FP&A teams) and Engineering, Product, and Operations teams in our Revenue Engine R&D pods to improve our revenue infrastructure and financial reporting. You will define the right questions, uncover opportunities, and work cross-functionally to turn insights into measurable improvements in how we track and report financial performance. In doing so, you will provide a timely and trusted view into company performance that shapes our customer experience and supports Headway's path to public company readiness. What You’ll Do: - Drive insights and decisions through strategic analysis, reporting, and predictive modeling.  - Design a metrics framework that connects our revenue infrastructure to financial outcomes, surfacing gaps in our data and reporting.  - Define and drive the measurement strategy for collections loss. Build the frameworks we use to understand where and why loss occurs, set targets for improvement, and identify the highest-ROI opportunities to reduce loss so they can be translated into cross-functional initiatives. - Build forecasts that inform staffing decisions and help us estimate how we’re tracking against goals.  - Partner cross-functionally to ensure our revenue systems provide the auditability and data traceability we need to be GAAP compliant and audit-ready.  - Translate complex technical findings into clear, actionable recommendations for executive stakeholders.  What We’re Looking For: - 10+ years of experience in data science or analytics roles. - Working knowledge of core finance and accounting concepts such as how transaction-level data powers financial reporting (P&L, balance sheet, and cash flow statement).  - Experience working with healthcare Revenue Cycle Management (RCM) is strongly preferred.  - Proven success partnering cross-functionally with Finance, Accounting, Product, Engineering, and Operations teams, and collaborating internally across Data Engineering and Data Science. - Proficiency in forecasting and predictive modeling techniques.  - Experience with data modeling, ideally using dbt.  - Hands-on technical fluency in SQL and Python or R. - Experience adopting a