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Applied Scientist II

Coalition - Any location, Canada

Posted Feb 24, 2026

Benefits

Parental leave
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Non-birth-parent leave
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Family-building benefits
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  • Adoption assistance: Not verified
  • Surrogacy assistance: Not verified
Mental health support
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Relocation assistance
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Childcare support
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Learning budget
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Market context

U.S. role benchmark (BLS OEWS)
$111,944 U.S. median for this role
Projected growth (BLS Employment Projections)
+13.7% - Much faster than average

Matched to SOC 15-1252 - Data and ML aggregate by role bucket.

Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.

Schedule

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Weekend work
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Application

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Assessment
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Deadline
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Where they hire

State eligibility is not yet verified.

About this role

Applied Scientist II Any location, Canada About us Coalition is the world's first Active Insurance provider designed to help prevent digital risk before it strikes. Founded in 2017, Coalition combines comprehensive insurance coverage and innovative cybersecurity tools to help businesses manage and mitigate potential cyberattacks. Opportunities to make an impact with bold thinking are real-and happening daily at Coalition. About the role We are hiring an Applied Scientist II to build and improve the machine learning and GenAI models that power our underwriting decisions. You will take ownership of high-impact modeling problems end-to-end. This includes framing and data exploration through model design, evaluation, deployment, and monitoring, directly influencing how we assess and price cyber risk. You'll work closely with underwriters, product managers, and engineers to design robust pipelines, experiment with state-of-the-art ML/GenAI techniques, and ship models that meaningfully move business metrics. Your work will turn complex insurance and security signals into reliable decisioning systems, helping Coalition write better business at scale while pushing the frontier of AI in underwriting. Responsibilities - Build and advance our most sensitive and business-critical ML and GenAI models that power underwriting decisions and risk selection. - Drive and execute ML projects end-to-end: problem framing, data exploration, feature engineering, model design, prototyping, offline/online evaluation, deployment, and monitoring. - Design and implement ML pipelines for data preprocessing, feature engineering, model training, hyperparameter tuning, and model evaluation, enabling rapid and reproducible experimentation. - Apply state-of-the-art ML and GenAI workflows (e.g., gradient-boosted trees, deep learning, LLMs, prompt engineering, transfer

Read the full description at www.coalitioninc.com. FewerJobs shows a source-linked preview and links to the original posting.

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