Data Scientist

Summary

Bold Penguin is a digital broker for commercial insurance that uses digital distribution, wholesale capabilities, and AI-driven insights to transform the lifecycle of insurance risks. The Data Scientist will design and deploy intelligent insurance products, including multi-agent AI systems, RAG pipelines, optimization models, and cloud-based machine learning solutions. The role also oversees data pipelines, statistical validation, and model retraining to support accurate and unbiased financial insights.

Responsibilities

• Apply mathematical optimization and portfolio theory to solve complex resource allocation and market placement problems
• Engineer Retrieval-Augmented Generation (RAG) pipelines and manage vector databases to provide real-time, context-aware intelligence
• Design and implement multi-agent systems and orchestration layers to automate complex, multi-step financial workflows
• Evaluate model performance using advanced statistical techniques to ensure accuracy in high-stakes financial scenarios
• Utilize AWS SageMaker and Bedrock to build, train, and scale machine learning models and agentic tools

Skills

• Education: Bachelor's or Master's degree in Computer Science, Data Science, Statistics, or a related quantitative field such as Financial Engineering
• Technical Expertise: Proven experience with Large Language Models (LLMs), agentic orchestration, and RAG architectures
• Quantitative Mastery: Solid understanding of optimization algorithms, statistical analysis, and machine learning principles
• Programming & Tools: Strong proficiency in Python and familiarity with AWS SageMaker and Bedrock
• Platform Experience: Proficiency with enterprise data science platforms such as RapidMiner (Altair) for automating financial data pipelines and risk modeling
• Problem Solving: Exceptional analytical skills with a focus on attention to detail and data integrity
• Collaboration: Strong communication skills and the ability to work effectively across technical and product teams
• Must be able to sit/stand/walk for prolonged periods of time, (up to 8 hours per day) at a desk working on a computer
• Must be able to use standard office equipment for extended periods of time, including but not limited to, a mouse, keyboard, phone and video conferencing
• Professional Experience: 3 to 5 years of experience as a Data Scientist, preferably within Financial Services, FinTech, or Property Risk Analytics
• This is a fully remote role, with the exception of onboarding and optional in-office events

Qualifications

Must Haves

• Education: Bachelor's or Master's degree in Computer Science, Data Science, Statistics, or a related quantitative field such as Financial Engineering
• Technical Expertise: Proven experience with Large Language Models (LLMs), agentic orchestration, and RAG architectures
• Quantitative Mastery: Solid understanding of optimization algorithms, statistical analysis, and machine learning principles
• Programming & Tools: Strong proficiency in Python and familiarity with AWS SageMaker and Bedrock
• Platform Experience: Proficiency with enterprise data science platforms such as RapidMiner (Altair) for automating financial data pipelines and risk modeling
• Problem Solving: Exceptional analytical skills with a focus on attention to detail and data integrity
• Collaboration: Strong communication skills and the ability to work effectively across technical and product teams
• Must be able to sit/stand/walk for prolonged periods of time, (up to 8 hours per day) at a desk working on a computer
• Must be able to use standard office equipment for extended periods of time, including but not limited to, a mouse, keyboard, phone and video conferencing

Nice to Haves

• Professional Experience: 3 to 5 years of experience as a Data Scientist, preferably within Financial Services, FinTech, or Property Risk Analytics
• This is a fully remote role, with the exception of onboarding and optional in-office events

Benefits

• Medical, Dental, and Vision
• Flexible PTO Policy
• 401(k) with a company match
• Employee Assistance Program
• Parental Leave
• Disability and Life Benefits
• Fully remote role, with the exception of onboarding and optional in-office events
• Employee swag