Applied Scientist II (GenAI)

TL;DR

Applied Scientist II (GenAI): Building and improving machine learning and GenAI models for underwriting decisions with an accent on problem framing, data exploration, feature engineering, model design, evaluation, deployment, and monitoring. Focus on applying state-of-the-art ML and GenAI workflows to improve underwriting accuracy and automation, and ensuring model quality and robustness.

Location: Remote (United States)

Salary: $115,900–$155,250/year

Company

hirify.global is the world's first Active Insurance provider, combining comprehensive insurance coverage and innovative cybersecurity tools to help businesses manage and mitigate potential cyberattacks.

What you will do

• Build and advance business-critical ML and GenAI models that power underwriting decisions and risk selection.
• Drive and execute ML projects end-to-end, including problem framing, data exploration, model design, evaluation, deployment, and monitoring.
• Design and implement ML pipelines for data preprocessing, feature engineering, model training, and evaluation.
• Apply state-of-the-art ML and GenAI workflows (e.g., gradient-boosted trees, deep learning, LLMs, prompt engineering) to improve underwriting accuracy and automation.
• Own model quality and robustness by defining success metrics, running diagnostics, and iterating to outperform baselines.
• Collaborate with underwriters, product, data, and engineering partners to clarify requirements and ensure models integrate cleanly into production.

Requirements

• Ph.D. or MS in a quantitative or computational field (e.g., Computer Science, Statistics, Applied Math, Electrical Engineering) or equivalent practical experience.
• 5+ years of full-time experience developing and deploying ML- and data-based solutions in production.
• Practical, hands-on experience with supervised and unsupervised learning methods, including model selection, regularization, and calibration.
• Expertise in statistical analysis methods, especially regression analysis, statistical inference, and forecasting/time-series.
• Strong proficiency in Python and core ML libraries (e.g., scikit-learn, XGBoost/LightGBM, PyTorch/TensorFlow) and SQL.
• Experience with experiment design and evaluation (e.g., A/B tests).
• Minimum 1+ year of experience in insurance underwriting modeling (pricing, risk scoring, eligibility, or related applications).
• English: B2 required.
• Must be based in the United States.

Nice to have

• Experience with modern GenAI techniques relevant to underwriting (e.g., using LLMs for document understanding or underwriter copilot workflows).
• Familiarity with model governance in regulated environments.
• Experience with ML orchestration and MLOps tools (e.g., Airflow, Prefect, MLflow, SageMaker).
• Exposure to causal inference or uplift modeling.
• Experience working with cyber or P&C insurance data.

Culture & Benefits

• 100% medical, dental, and vision coverage.
• Flexible PTO policy.
• Annual home office stipend and WeWork access.
• Mental & physical health wellness programs (One Medical, Headspace, Wellhub, and more).
• Competitive compensation and opportunity for advancement.
• Remote-first, highly inclusive culture focused on protecting businesses from digital risk.