Senior Data Scientist: ML, NLP & MLOps Leader

Richmond National; Glen Allen (VA); On-site; USD 120,000 - 130,000; Full time

Benefits offered by this job

Medical, dental, vision

FSA/HSA plans

Life/AD&D/Disability insurance

401(k) company match up to 6%

Flexible PTO + 11 holidays + birthday

Top Workplace recognition

Job summary

Richmond National Insurance Company is seeking an experienced Sr. Data Scientist to lead data product development and ML initiatives.

You will design, deploy, and maintain scalable data pipelines and ML models, collaborating with engineers, analysts, and stakeholders to drive data-driven decisions. The role requires 5+ years in data science with expertise in ML, NLP, and LLM-based applications, plus strong SQL/Python and cloud experience.

Qualifications

• 5+ years in data science roles, preferably in insurance/finance
• Strong ML, statistical modeling, and AI knowledge
• Proficient in SQL, Python, Excel
• Experience with LLMs, NLP, and vision-language models
• Good data modeling, ETL, and data integration skills
• Proficient in Python/Java/Scala and SQL
• Experience with AWS ML services (SageMaker/Bedrock) and data visualization
• Strong communication and collaboration skills

Responsibilities

• Build and maintain scalable ML pipelines and MLOps infrastructure.
• Develop custom ML models and tune foundational models.
• Monitor model performance and accuracy; implement governance.
• Ensure data privacy and security in collaboration with IT leadership.
• Collaborate with cross-functional teams to deliver data-driven solutions.
• Stay updated on industry trends and adopt new tools.
• Document ML/AI pipelines and workflows for stakeholders.

Skills

ML modeling

NLP

Vision-Language Models

Python

Java

Scala

SQL

Excel

AWS ML/AI services

Tools

SageMaker

Bedrock

Job description

Richmond National Insurance Company is seeking an experienced Sr. Data Scientist to lead data product development and ML initiatives.

You will design, deploy, and maintain scalable data pipelines and ML models, collaborating with engineers, analysts, and stakeholders to drive data-driven decisions. The role requires 5+ years in data science with expertise in ML, NLP, and LLM-based applications, plus strong SQL/Python and cloud experience.