Job Specifications
Title: Sr. ML Engineer
Location: Palm Beach, Florida (Hybrid, 3 days a week on-site)
Type: Full-Time Opportunity
Pay Range: Up to $145,000
Eligibility: U.S. Citizenship or Green Card required
Experience in insurance, particularly in Commercial or Specialty (Property & Casualty) lines, preferred.
No third parties
Overview:
The Senior Machine Learning Engineer will play a strategic role in shaping AI and data engineering initiatives across the organization. This position requires a seasoned professional capable of leveraging advanced analytics, machine learning models, and data engineering best practices to drive insights, optimize business processes, and enhance decision-making. Experience within the commercial insurance sector is highly desirable due to the data-rich and complex nature of the environment.
Key Responsibilities:
AI Engineering & Integration
Build and maintain reliable ETL pipelines using AWS services (Glue, Redshift, S3, Lambda, Aurora) to support the enterprise data warehouse.
Design LLM-based data flows for policy and claims ingestion, developing mapping profiles for new data sources.
Ensure high data quality through validation, monitoring, and anomaly detection processes.
Collaborate with leadership to define and implement a comprehensive data strategy aligned with organizational goals.
Oversee release management and integration of data science solutions into production.
Conduct ad-hoc reporting, statistical analysis, and data-driven investigations to support business operations.
Innovation and Continuous Improvement
Identify, design, and implement predictive and prescriptive ML algorithms to optimize underwriting, claims management, risk assessment, and client engagement.
Build and maintain feature stores to improve ML project efficiency.
Lead data strategy development and oversee deployment of production-grade ML solutions.
Champion peer-review processes to maintain code quality and modeling excellence.
Governance and Compliance
Establish and enforce data governance standards ensuring compliance with regulatory requirements.
Maintain CI/CD pipelines via GitHub with full documentation and peer review.
Monitor emerging technologies and industry trends to enhance data and analytics capabilities.
Core Responsibilities (General)
Develop machine learning, optimization, and modeling solutions.
Prepare and document analyses, technical reports, and quantitative findings.
Work with big data and distributed computing platforms.
Contribute to software development and product enhancement efforts.
Perform additional job-related duties as assigned.
Skills Needed:
Bachelor's degree and a Master's or Ph.D. in Physics, Mathematics, Computer Science, or a related field (preferred)
7+ years of hands-on experience with Python, SQL, NoSQL, and Git-based workflows.
7+ years of experience with AWS services (Glue, Redshift, S3, Lambda, Aurora).
Strong expertise in database design, data warehousing, ETL development, and distributed data systems.
Proven background in machine learning, predictive modeling, statistical analysis, and data mining.
Familiarity with data visualization tools such as Power BI or Grafana.
Experience in insurance, particularly in Commercial or Specialty (Property & Casualty) lines, preferred.
Exposure to program insurance or delegated authority models is a plus.
Strong Agile/Scrum experience for project management in collaborative environments.
AINS designation or equivalent insurance certification preferred.
To be considered for this role, please apply online or email an updated resume to Rachel Place at Oliver James - Rachel.place@oliverjames.com.
About the Company
We introduce talented people to great organisations so that both may grow and benefit from each other’s experiences, helping to fulfil their potential.
We understand that each client’s mix of people, culture, and objectives is unique, so our approach and solutions are flexible and adapted to each person, team, company, and situation.
Although your relationship with OJ is with your local consultant(s), their network, relationships, and knowledge of diverse local candidate pools are backed by those of their local permanent...
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