Most of what makes American healthcare expensive isn’t medical care. It’s the machinery wrapped around it: middlemen taking a cut, fraud nobody stops, and billing systems designed to fight over payment instead of deliver care. The result is higher premiums, denied claims, surprise bills, and a system patients increasingly experience as adversarial.
Arlo is rebuilding health insurance for small businesses from first principles: making sure as much of every premium dollar as possible goes to care instead of getting absorbed by the system around it. We do that by identifying fraud earlier, steering members toward higher-quality and lower-cost care, automating operational overhead, and eliminating vendors whose business exists mostly to take a cut.
AI is the foundation that makes this work. We use it across underwriting, operations, clinical programs, and member experience to build an insurer that becomes more efficient as the technology improves.
We’re already operating at meaningful scale: profitable, hundreds of millions in premiums, tens of thousands of members covered, and growing quickly through brokers, employers, and partners. Backed by Upfront Ventures, 8VC, and General Catalyst, with a team from Palantir, YC companies, and longtime healthcare operators.
As the VP of Clinical Strategy & Population Health, you’ll be responsible for designing the clinical foundation of Arlo’s health plans—making care more affordable, accessible, and high-quality for our members nationwide. You’ll work across product, actuarial, and operations functions to define population health strategies, develop partnerships with providers, and build models that deliver better outcomes at lower costs.
Some initiatives you will lead:
Health Plan Design: Shape plan structures that drive preventive care, reduce wasteful spend, and promote high-value care. You’ll use data and clinical insight to design benefit structures that actually make people healthier.
Population Health Strategy: Identify key needs across Arlo’s member populations and develop scalable, data-driven programs to improve outcomes and reduce the total cost of care.
Care Navigation Models: Help guide how Arlo’s concierge and care support services proactively engage members—especially those with complex or rising risk conditions.
Condition-Focused Programs: Use Arlo's claims history to identify where members need the most support—such as diabetes, MSK, and oncology—and design targeted clinical programs to address them. You'll decide where it makes sense to build in-house versus partner with specialized vendors.
Integrated Care Delivery: Explore models that let Arlo take a more direct role in members' primary care experience—deepening the patient-provider relationship and giving us greater ability to influence quality, continuity, and cost of care.
Provider Partnerships: Build relationships with value-based providers, specialist networks, and health systems. Craft incentive structures that align economic outcomes with quality improvement.
Clinical Voice: Serve as the clinical expert in product, claims, and underwriting discussions—ensuring that decisions are backed by sound medical reasoning and real-world impact.
Clinical Background: You have a clinical degree (e.g., MD, DO, RN, NP, MPH) and experience working directly with patients or health systems.
Population Health Experience: You’ve developed or led population health programs or value-based care models in a health plan, provider group, or ACO.
Health Plan Design Acumen: You understand how health plan structures impact member behavior and provider incentives—and have ideas for doing it better.
Strong Communication Skills: You can translate clinical insights into business recommendations and vice versa. You’re just as comfortable in a product roadmap meeting as in a clinical roundtable.
Bias for Impact: You like to build. You’re comfortable working in ambiguous environments and excited by the opportunity to shape a health plan from the ground up. You are happy to take partner meetings and proactively turn your ideas into reality.
Data Driven: You have experience working with claims data and can derive data-driven strategies and action plans based on it.
Startup Curiosity (or Experience): You’ve worked in or closely with early-stage companies—or want to in the future.
This is what you can expect when we like your application:
30 minute conversation with Rachelle (Talent Lead)
45-minute introductory call with Karthik (CTO/COO & Co-Founder)
Take-home case study
30-minute review of your case study (virtual)
Onsite interview at our NYC office (or virtual for remote), including behavioral/cultural components
High ownership: You’ll get real responsibility from day one—our high-trust team empowers you to run with big problems and shape core parts of the company.
Join an important mission: Your work directly influences how people access care and improves lives at scale.
Growth & expansion: We’re moving fast, and as we grow, your scope will grow with us—new challenges, bigger opportunities, and rapid career velocity.
Apply AI to a problem that matters: Instead of optimizing ads or cutting labor costs, you’ll use AI to fundamentally reimagine how people get healthcare.
High pace, high collaboration: We operate with velocity, first-principles thinking, and a team that works closely, openly, and with ambition.
Exact compensation inclusive of salary and any bonuses is determined based on a number of factors including experience and skill level, location, and qualifications which are assessed during the interview process.
Arlo is an equal opportunity employer. We do not discriminate based on age, race, color, creed or religion, national origin, sexual orientation, gender identity or expression, military status, sex, disability, predisposing genetic characteristics, marital status, familial status, status as a victim of domestic violence, or arrest or conviction record, as defined under New York State law.
🔒 Your safety matters to us. If you're selected to move forward in our hiring process, you'll hear directly from a member of our Recruiting team via an @joinarlo.com email address. We will never ask for personal or financial information outside of our formal onboarding process. When in doubt, please reach out to us to verify at: recruiting@joinarlo.com.
Most of what makes American healthcare expensive isn’t medical care. It’s the machinery wrapped around it: middlemen taking a cut, fraud nobody stops, and billing systems designed to fight over payment instead of deliver care. The result is higher premiums, denied claims, surprise bills, and a system patients increasingly experience as adversarial.
Arlo is rebuilding health insurance for small businesses from first principles: making sure as much of every premium dollar as possible goes to care instead of getting absorbed by the system around it. We do that by identifying fraud earlier, steering members toward higher-quality and lower-cost care, automating operational overhead, and eliminating vendors whose business exists mostly to take a cut.
AI is the foundation that makes this work. We use it across underwriting, operations, clinical programs, and member experience to build an insurer that becomes more efficient as the technology improves.
We’re already operating at meaningful scale: profitable, hundreds of millions in premiums, tens of thousands of members covered, and growing quickly through brokers, employers, and partners. Backed by Upfront Ventures, 8VC, and General Catalyst, with a team from Palantir, YC companies, and longtime healthcare operators.
As a Member Advocate, you’ll be the first point of contact for members, responding to questions and concerns with empathy and professionalism across text, email, and live messaging. You’ll take ownership of each interaction—helping members navigate their health insurance, benefits, and claims from start to finish. You’ll also work closely with teams across Sales, Product, Operations, and Engineering to continuously improve the member experience. Your goal: to ensure every member feels heard, supported, and confident in their care.
You’re best suited to this role if you thrive on solving problems for others, communicate clearly and kindly, and enjoy working across teams to create a better experience for everyone.
Your key focus areas will include:
Member Experience: Deliver fast, thoughtful chat-based support that builds trust and confidence.
Issue Resolution: Take ownership of problems, drive them to resolution, and follow through with clear communication.
Cross-Functional Collaboration: Work with internal teams to surface insights and improve systems and workflows.
Process Improvement: Identify patterns, inefficiencies, or recurring questions and contribute to better tools, resources, and documentation.
1-3 years of customer service experience in a health plan/health insurance environment
Strong written and verbal communication skills, with the ability to explain complex topics quickly, clearly, and empathetically.
Comfort using multiple channels and tools (e.g., CRM systems, chat platforms, text, and email support).
Detail-oriented and organized, with strong follow-through and problem-solving skills.
Ability to manage multiple tasks in a fast-paced environment while maintaining a positive member experience.
Passion for helping people and improving the healthcare experience.
Availability to work an 8 hour shift within the timeframe of 8:30 AM – 6:00 PM Eastern Time, with preference given to candidates in Eastern or Central time zones.
Nice to Have:
Experience in care management / clinical care coordination
High ownership: You’ll get real responsibility from day one—our high-trust team empowers you to run with big problems and shape core parts of the company.
Join an important mission: Your work directly influences how people access care and improves lives at scale.
Growth & expansion: We’re moving fast, and as we grow, your scope will grow with us—new challenges, bigger opportunities, and rapid career velocity.
Apply AI to a problem that matters: Instead of optimizing ads or cutting labor costs, you’ll use AI to fundamentally reimagine how people get healthcare.
High pace, high collaboration: We operate with velocity, first-principles thinking, and a team that works closely, openly, and with ambition.
Exact compensation inclusive of salary and any bonuses is determined based on a number of factors including experience and skill level, location, and qualifications which are assessed during the interview process.
Arlo is an equal opportunity employer. We do not discriminate based on age, race, color, creed or religion, national origin, sexual orientation, gender identity or expression, military status, sex, disability, predisposing genetic characteristics, marital status, familial status, status as a victim of domestic violence, or arrest or conviction record, as defined under New York State law.
🔒 Your safety matters to us. If you're selected to move forward in our hiring process, you'll hear directly from a member of our Recruiting team via an @joinarlo.com email address. We will never ask for personal or financial information outside of our formal onboarding process. When in doubt, please reach out to us to verify at: recruiting@joinarlo.com.
Most of what makes American healthcare expensive isn’t medical care. It’s the machinery wrapped around it: middlemen taking a cut, fraud nobody stops, and billing systems designed to fight over payment instead of deliver care. The result is higher premiums, denied claims, surprise bills, and a system patients increasingly experience as adversarial.
Arlo is rebuilding health insurance for small businesses from first principles: making sure as much of every premium dollar as possible goes to care instead of getting absorbed by the system around it. We do that by identifying fraud earlier, steering members toward higher-quality and lower-cost care, automating operational overhead, and eliminating vendors whose business exists mostly to take a cut.
AI is the foundation that makes this work. We use it across underwriting, operations, clinical programs, and member experience to build an insurer that becomes more efficient as the technology improves.
We’re already operating at meaningful scale: profitable, hundreds of millions in premiums, tens of thousands of members covered, and growing quickly through brokers, employers, and partners. Backed by Upfront Ventures, 8VC, and General Catalyst, with a team from Palantir, YC companies, and longtime healthcare operators.
Arlo's underwriting is the core of the business, and it runs on machine learning at serious scale. We're hiring a Senior ML Engineer to build and own the infrastructure that powers it — from training models on tens of millions of patients and hundreds of millions of rows of claims data, to serving real-time quotes in seconds against inference-time datasets that run into the trillions of rows. You'll also build the tooling that lets our data scientists and actuaries iterate faster than ever.
This is an ML role with real room to do ML and data science. You'll own the platform, but you'll also have the opportunity to work alongside our data scientists and actuaries to test and evaluate your own ideas — not just support theirs.
Training infrastructure for underwriting
Build and own the infrastructure layer that powers our underwriting model, trained on tens of millions of patients and hundreds of millions of rows of claims data.
Make training reliable, reproducible, and scalable as data volume and model complexity grow.
Real-time inference for quoting
Build and own the API layer that produces quotes in seconds — serving a trained model against a much larger inference-time dataset, on the order of trillions of rows of claims across hundreds of millions of people.
Own the latency, reliability, and scalability of the serving path the quoting product depends on.
Accelerate data science iteration
Make it as easy as possible for data scientists and actuaries to test new features and ideas.
Build backtesting and validation infrastructure so model performance can be measured quickly and trustworthily.
Remove friction from the path between an idea and a validated, production-ready model — make experimentation simpler than it's ever been.
A strong track record building ML or data infrastructure in production at scale.
Deep proficiency in Python, with comfort in processing large datasets (Spark, Databricks, or equivalent).
Experience with model training pipelines and/or low-latency model serving in production.
Experience building tooling that makes other people faster — feature testing, experiment tracking, backtesting, or similar developer/researcher-facing infrastructure.
The ability to own systems end-to-end, set standards, and operate reliable production infrastructure (SLAs, monitoring, on-call).
Genuine interest in the modeling itself — you want to occasionally get your hands into the data science, not only the infrastructure.
Prior experience in a regulated space like healthcare or insurance.
Experience with MLOps tooling (MLflow or similar), feature stores, or experimentation platforms.
Experience supporting data science or actuarial teams in production environments.
$180,000 – $230,000 + equity
High ownership: You’ll get real responsibility from day one—our high-trust team empowers you to run with big problems and shape core parts of the company.
Join an important mission: Your work directly influences how people access care and improves lives at scale.
Growth & expansion: We’re moving fast, and as we grow, your scope will grow with us—new challenges, bigger opportunities, and rapid career velocity.
Apply AI to a problem that matters: Instead of optimizing ads or cutting labor costs, you’ll use AI to fundamentally reimagine how people get healthcare.
High pace, high collaboration: We operate with velocity, first-principles thinking, and a team that works closely, openly, and with ambition.
Exact compensation inclusive of salary and any bonuses is determined based on a number of factors including experience and skill level, location, and qualifications which are assessed during the interview process.
Arlo is an equal opportunity employer. We do not discriminate based on age, race, color, creed or religion, national origin, sexual orientation, gender identity or expression, military status, sex, disability, predisposing genetic characteristics, marital status, familial status, status as a victim of domestic violence, or arrest or conviction record, as defined under New York State law.
🔒 Your safety matters to us. If you're selected to move forward in our hiring process, you'll hear directly from a member of our Recruiting team via an @joinarlo.com email address. We will never ask for personal or financial information outside of our formal onboarding process. When in doubt, please reach out to us to verify at: recruiting@joinarlo.com.
Most of what makes American healthcare expensive isn’t medical care. It’s the machinery wrapped around it: middlemen taking a cut, fraud nobody stops, and billing systems designed to fight over payment instead of deliver care. The result is higher premiums, denied claims, surprise bills, and a system patients increasingly experience as adversarial.
Arlo is rebuilding health insurance for small businesses from first principles: making sure as much of every premium dollar as possible goes to care instead of getting absorbed by the system around it. We do that by identifying fraud earlier, steering members toward higher-quality and lower-cost care, automating operational overhead, and eliminating vendors whose business exists mostly to take a cut.
AI is the foundation that makes this work. We use it across underwriting, operations, clinical programs, and member experience to build an insurer that becomes more efficient as the technology improves.
We’re already operating at meaningful scale: profitable, hundreds of millions in premiums, tens of thousands of members covered, and growing quickly through brokers, employers, and partners. Backed by Upfront Ventures, 8VC, and General Catalyst, with a team from Palantir, YC companies, and longtime healthcare operators.
About the role:
Underwriting is at the core of Arlo. Every group we price depends on how accurately we can estimate the risk of the individual members inside, and the quality of the estimate is essential to the sustainability of our business. We’re hiring a Senior Data Scientist to own our underwriting model and continuously deploy measurable improvements to it based on learnings from real-world outcomes. You’ll work with billions of claims across tens of millions of patients to identify what signals in claims history predict future medical cost, how to roll it up to a competitive price for a group, and how to deploy the system at scale. You’ll constantly monitor the lifecycle of predictions, group policies sold, and claims incurred by our tens of thousands of members to gather novel insights that can improve our model and pricing approach.
This is a hands-on modeling role in which you will sit on the underwriting team alongside our team of data scientists and actuaries thinking through issues beyond point estimates of cost including how to handle data blindness, variability, and when the risk is too high to issue a quote. You’ll own the model but work alongside ML engineers to ensure that your ideas can be tested and deployed at scale.
What you’ll work on:
Evaluate the existing Arlo underwriting model and find where it breaks
Develop a robust evaluation framework to stress the model outcomes and identify specific gaps in risk estimates (cohorts, conditions, or claims patterns) and the underlying causal factors
Use those findings to generate a roadmap of model and feature work that is prioritized based on making sure our rates are competitive in the market while ensuring we can remain a profitable business.
Build features that capture the full risk of a member
Account for training and inference dataset bias to optimize member predictions
Improve handling of member cost variance in our quoting pipeline
Experiment with model designs
Implement different ML architectures that balance efficacy, generalizability, and understanding so we can outperform the market
Prove the lift before it ships
Work with our backtesting harness to measure the effect of every model change on MLR and competitiveness.
Set the bar for what \"better\" means and hold changes to it, so improvements to the model are trustworthy
What we’re looking for:
5+ years as a data scientist building predictive models that made it into production
Deep proficiency in Python and SQL, with comfort processing large datasets using Spark and using common modeling packages.
A track record of owning a problem end-to-end in an ambiguous environment and shipping without being handed a spec
Direct experience with healthcare data
Strong instincts for feature engineering and model validation, and the judgment of how well results might be able to hold in production
Interest in the larger business context. This is not a research endeavor, but a live model that directly changes our win rates, book size, and performance.
Clear communicator who can explain what they did and why it mattered
Nice to Have:
Familiarity with claims data and their known quirks and biases
Prior experience working at Series C or earlier start-ups
Background in underwriting, actuarial sciences, or risk adjustments
Experience with ML engineering and infrastructure
Compensation
$170,000- $220,000 + equity and benefits
High ownership: You’ll get real responsibility from day one—our high-trust team empowers you to run with big problems and shape core parts of the company.
Join an important mission: Your work directly influences how people access care and improves lives at scale.
Growth & expansion: We’re moving fast, and as we grow, your scope will grow with us—new challenges, bigger opportunities, and rapid career velocity.
Apply AI to a problem that matters: Instead of optimizing ads or cutting labor costs, you’ll use AI to fundamentally reimagine how people get healthcare.
High pace, high collaboration: We operate with velocity, first-principles thinking, and a team that works closely, openly, and with ambition.
Exact compensation inclusive of salary and any bonuses is determined based on a number of factors including experience and skill level, location, and qualifications which are assessed during the interview process.
Arlo is an equal opportunity employer. We do not discriminate based on age, race, color, creed or religion, national origin, sexual orientation, gender identity or expression, military status, sex, disability, predisposing genetic characteristics, marital status, familial status, status as a victim of domestic violence, or arrest or conviction record, as defined under New York State law.
🔒 Your safety matters to us. If you're selected to move forward in our hiring process, you'll hear directly from a member of our Recruiting team via an @joinarlo.com email address. We will never ask for personal or financial information outside of our formal onboarding process. When in doubt, please reach out to us to verify at: recruiting@joinarlo.com.