Lead Data Science Engineer

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.

Arlos founding team has extensive experience in claims analytics data science benefits administration systems and health plan underwriting. Arlos 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.

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.

• 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

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

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 members 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.

NYC onsite

Be aware: this is NOT a remote position

At Arlo were 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 peoples full potential. Were building an employee experience that includes appreciation belonging growth and purpose for everyone.

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 or apply via the form.

Required Experience:

Senior IC