Remote Principal: Real-Time ML for Payments

Eliassen Group; Boise (ID); Remote; USD 242,458,000 - 272,765,000; Full time

Benefits offered by this job

Medical, Dental, and Vision benefits

401k with company matching

Life insurance

Job summary

Eliassen Group is seeking a Principal Data Scientist to scale AI capabilities for real-time payment optimization. You will collaborate with ML engineers and product partners to design and deploy real-time models and intelligent decision engines, driving strategy and roadmaps while mentoring senior data scientists.

The role combines strategic leadership with hands-on contribution across architecture, design reviews, and deployment of production-grade ML solutions.

Qualifications

• 7+ years in ML research or engineering with 5+ years building large-scale, real-time ML systems in production.
• Proficiency in Python and SQL; NoSQL or graph databases are a plus.
• Strong communication skills with ability to influence across technical and business audiences.

Responsibilities

• Define technical vision and strategy for data-driven product initiatives focused on payment optimization.
• Develop scalable real-time ML models including classification, ranking, and optimization.
• Oversee end-to-end ML model lifecycle, deployment, and monitoring.
• Establish best practices for ML modeling and evaluation.
• Mentor and guide senior data scientists.
• Collaborate with product, engineering, data, and compliance teams to integrate ML into products.
• Partner with DS leaders to optimize end-to-end ML delivery.

Skills

Python

SQL

Machine Learning

Real-time ML systems

Leadership

Communication

Payments domain knowledge

Education

Bachelor's or Master's degree in a related field

PhD preferred

Tools

AWS

GCP

Snowflake

Databricks

Vertex AI

Job description

Eliassen Group is seeking a Principal Data Scientist to scale AI capabilities for real-time payment optimization. You will collaborate with ML engineers and product partners to design and deploy real-time models and intelligent decision engines, driving strategy and roadmaps while mentoring senior data scientists.

The role combines strategic leadership with hands-on contribution across architecture, design reviews, and deployment of production-grade ML solutions.