Forward Deployed Insights Engineer
Wintermeyer Ventures
New York, NY, United States
16 days ago
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Role details
Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Experienced
Experience required
3 years minimum
Compensation
$180,000.0 - $230,000.0
Working hours
Regular working hours
Job source
Tech stack
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
+5 more
Apache Spark
Agentic-AI
Git Flow
Data Pipelines
Databricks
Job 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.
Requirements
- 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.
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