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# Forward Deployed Insights Engineer

- **Company:** Wintermeyer Ventures
- **Location:** New York, NY, United States
- **Experience:** Experienced
- **Salary:** $180,000.0 - $230,000.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Data Analysis, Continuous Integration, Data Infrastructure, Distributed Systems, Python (Programming Language), Machine Learning, Standard Sql, Software Deployment, SQL Databases, Large Language Models, Snowflake, Apache Spark, Agentic-AI, Git Flow, Data Pipelines, Databricks
- **Published:** October 18, 2026
- **Apply:** https://www.careerjet.com/jobad/usa0dd4949c5546bdf90b5e506d27210bf

## About the Role

* Three to ten years of experience in data science, applied machine learning, or analytics.
 * Experience shipping predictive models, applied machine learning systems, or AI agents to production for customers, with end-to-end ownership.
 * Hands-on experience building and evaluating LLM-based agents, along with strong Python and SQL skills.
 * Customer-facing technical experience, such as forward deployment or implementation work with end users.
 * Healthcare administration or finance experience with areas such as claims, eligibility, revenue cycle management, EHR, or payer and provider operations data. Background should be focused on administrative or financial workflows rather than clinical practice.
 * A bachelor's degree in a quantitative field or equivalent applied machine learning experience.
 * Experience with data pipelines, distributed computing, or cloud platforms, such as Snowflake, Databricks, or Spark, and ownership of CI/CD and Git workflows.

## Description

Join a team building AI software for healthcare finance. You will work directly with customers to apply AI and machine learning to complex data and workflows, helping turn technical capabilities into useful, trusted decisions.
What You'll Do

 * Build, configure, and evaluate AI agents to address specific healthcare finance problems.
 * Create visualizations that help customers understand data and make informed decisions.
 * Work directly with end users to understand their needs and translate them into technical solutions.
 * Take applied AI and machine learning projects from development through production deployment for customers.
 * Use Python, SQL, and relevant data infrastructure to support reliable solutions and workflows.