About Arlo
Arlo powers healthcare innovation through modern underwriting technology. Small and medium-sized businesses have long seen little innovation in their health plan options and are hit with ever-increasing healthcare costs. As a technology-forward MGU (managing general underwriter), we use modern data science techniques to help health plan architects design novel health plans and leverage value-based care. Our mission is to bring affordable, value-based health benefits to employees of small and medium-sized businesses nationwide.Arlo’s founding team has extensive experience in claims analytics, data science, benefits administration systems, and health plan underwriting.
Arlo’s team members previously worked at Palantir, Willis Towers Watson, McKinsey, and a Y-Combinator startup. Arlo has raised a $4M seed round from Upfront Ventures, 8VC, and General Catalyst.At Arlo, we value diverse opinions and debate. We are team-focused learners and seek to understand the missing perspective. Our team is collaborative, ambitious, and passionate about advancing the future of healthcare.We are looking for a motivated team member to join us locally in NYC.
Team Overview & Role Impact
As a Data Science Engineer, you will own the next iterations of the Arlo underwriting API from modeling to deployment. You will partner closely with our head actuary to refine our model and ideate novel underwriting strategies.
Responsibilities
Define and manage the architecture of the Arlo data and machine learning deployment pipelines
Setup a system to manage and maintain the Arlo underwriting models
Design and implement reporting tools from quote data and in-force business
Support the next development iterations of the Arlo underwriting approach
Deploy the Arlo underwriting models into our production environment
Evaluate new data sources for health underwriting and use SDOH features to predict health outcomes
Qualifications & Experience
Required
2+ years working as a data scientist or engineer
Experience setting up and managing large data pipelines
Experience working with standard machine learning techniques
Experience setting up production-ready API services for model evaluations
An interest in using the best tool for the job. Our current favorites are Python, Sklearn, SQL, PySpark, SparkML, Snowpark, Python API frameworks, AWS, Docker
Nice to Haves
Familiarity with health insurance industry and financial terminology
Experience working with medical and prescription drug claims data
Experience working with probabilistic modeling techniques
Experience working with social determinants of health data sources
Our Culture
We cultivate a high-performance culture. We greatly care about the work we do and have a passion for solving the “unsexy” parts of healthcare infrastructure. We strongly believe that addressing these problems is a key enabler for unlocking affordable, high-quality care.We value collaboration, a high sense of ownership for every team member's work, and getting things done quickly and efficiently. We are curious and love to learn as we push the boundaries in an industry often devoid of first-principle thinking.We are ambitious and are on a mission to build an industry-defining company.
Location
NYC onsiteBe aware: this is NOT a remote position
Equal Employer Opportunity Statement
At Arlo, we’re challenging the status quo with the power of diversity, inclusion, and collaboration. When we connect different perspectives, we can imagine new possibilities, inspire innovation, and release our people's full potential. We’re building an employee experience that includes appreciation, belonging, growth, and purpose for everyone.
Compensation & Benefits
We offer a competitive base salary and meaningful equity in Arlo. We also offer medical coverage, unlimited paid time off, free lunches on workdays in the office, a stipend for professional development, company-wide off-sites, 16 weeks of fully paid parental leave, and biannual performance reviews with 360° feedback.Please send your application to team@joinarlo.com or apply via the form.
Compensation:USD 140000-175000
