Machine Learning Engineer

Job Description

Our client, a major insurance and financial services institution, is seeking a Machine Learning Engineer to support the development and delivery of data-driven solutions across key initiatives. The role focuses on building and maintaining data pipelines, enabling analytics, and deploying production-ready solutions that support decision‑making across insurance and wealth management functions.

This role sits at the intersection of data engineering and applied machine learning, where you will help transform complex, multi‑source data into scalable solutions and actionable insights. You’ll collaborate closely with cross‑functional teams to understand business needs, operationalize models, and improve how data is leveraged across the organization.

Hybrid opportunity in Boston, MA.

• Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related field (or equivalent experience)
• 4+ years of experience in data engineering, analytics engineering, or machine learning engineering roles
• Strong programming skills in Python and/or other modern languages
• Advanced SQL skills and experience working with relational databases
• Experience building and maintaining data pipelines and workflows
• Experience transforming and preparing data for analytics and reporting
• Familiarity with data visualization tools (e.g., Tableau, Power BI, or similar)
• Strong analytical and problem‑solving skills
• Ability to work with complex datasets across multiple systems
• Strong communication skills with the ability to translate technical concepts into business terms

• Experience deploying or supporting machine learning models in production environments
• Familiarity with large‑scale or distributed data processing environments
• Understanding of structured and unstructured data systems
• Exposure to statistical modeling or machine learning techniques
• Familiarity with modern data modeling approaches
• Experience with in insurance, financial services, or wealth management environments
• Ability to explore large datasets and generate actionable insights
• Experience mentoring junior team members

• Build, maintain, and optimize data pipelines to support analytics and model deployment
• Partner with stakeholders to identify, access, and understand data sources
• Transform and stage data for analytics, reporting, and data science use cases
• Support deployment and monitoring of machine learning solutions
• Develop and manage datasets, tables, and database structures
• Perform data analysis to generate insights and business recommendations
• Translate technical findings into clear, actionable insights for stakeholders
• Collaborate with data scientists and engineers to product ionize solutions
• Measure and evaluate performance of models and data‑driven solutions
• Mentor junior team members and contribute to team best practices
• Document workflows, datasets, and processes

• 30% Data Engineering & Pipeline Development
• 25% Machine Learning Support & Productionization
• 20% SQL & Data Transformation
• 15% Analytics & Visualization
• 10% Stakeholder Collaboration

• 65% Hands‑On Development & Data Work
• 20% Analysis & Insight Generation
• 15% Team Collaboration & Communication

• Bonus eligible

• Medical Insurance
• Dental Benefits
• Vision Benefits
• Paid Time Off (PTO)
• 401(k) (including match, if applicable)

Applicants must be currently authorized to work in the US on a full‑time basis now and in the future.

Posted By: Sarah Carroll