Senior Data Scientist

Arlo • New York, NY

11d • $170,000 - $220,000

About The Position

Arlo is rebuilding health insurance for small businesses by focusing on ensuring that a larger portion of premium dollars goes towards care rather than administrative costs. They achieve this by identifying fraud, guiding members to better and more affordable care, automating operations, and eliminating unnecessary vendors. Artificial intelligence is central to their strategy, used across underwriting, operations, clinical programs, and member experience to create a more efficient insurance model. The company operates at a significant scale, is profitable, handles hundreds of millions in premiums, covers tens of thousands of members, and is experiencing rapid growth. They are backed by prominent venture capital firms and have a team composed of individuals from Palantir, YC companies, and experienced healthcare professionals.

This role is crucial as underwriting is fundamental to Arlo's business. The accuracy of risk estimation for individual members directly impacts the sustainability of the business. The Senior Data Scientist will be responsible for the underwriting model, continuously improving it based on real-world outcomes. This involves analyzing vast amounts of claims data to identify predictors of future medical costs, developing competitive group pricing strategies, and deploying these systems at scale. The position requires ongoing monitoring of prediction lifecycles, policy sales, and incurred claims to derive insights for model and pricing enhancements. It is a hands-on modeling role within the underwriting team, collaborating with data scientists and actuaries on complex issues beyond simple cost estimates, such as data limitations, variability, and risk assessment for quoting. While owning the model, the role involves close collaboration with ML engineers to ensure ideas can be tested and deployed effectively at scale.

Requirements

• 5+ years of experience as a data scientist building predictive models that have been deployed to production.
• Deep proficiency in Python and SQL.
• Comfort processing large datasets using Spark.
• Experience with common modeling packages.
• A proven ability to own a problem end-to-end in an ambiguous environment and deliver results without a predefined specification.
• Direct experience working with healthcare data.
• Strong skills in feature engineering and model validation.
• Sound judgment regarding the production viability of results.
• Interest in the broader business context; the role is focused on a live model impacting win rates, book size, and performance, not purely research.
• Clear communication skills to explain methodologies and their impact.

Nice To Haves

• Familiarity with claims data, including its known quirks and biases.
• Prior experience working at Series C or earlier stage startups.
• Background in underwriting, actuarial sciences, or risk adjustment.
• Experience with ML engineering and infrastructure.

Responsibilities

• Evaluate the existing Arlo underwriting model and identify its weaknesses.
• Develop a robust evaluation framework to test model outcomes and pinpoint specific gaps in risk estimates (e.g., cohorts, conditions, claims patterns) and their underlying causes.
• Create a prioritized roadmap for model and feature development based on findings, balancing market competitiveness with business profitability.
• Build features that accurately capture a member's full risk profile.
• Address biases in training and inference datasets to optimize member predictions.
• Enhance the handling of member cost variance within the quoting pipeline.
• Experiment with and implement different ML architectures that balance effectiveness, generalizability, and interpretability to outperform the market.
• Measure the impact of every model change on MLR and competitiveness using the backtesting harness before deployment.
• Establish clear metrics for improvement and ensure changes adhere to them, maintaining trust in the model.

Benefits

• Equity
• Health insurance
• High ownership with real responsibility from day one.
• Opportunity to work on an important mission that directly influences healthcare access and improves lives.
• Growth and expansion opportunities with increasing scope and career velocity.
• Application of AI to fundamentally reimagine healthcare.
• High pace and high collaboration environment with velocity and first-principles thinking.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed