Principal Data Scientist - Real-Time Payments AI (Remote)

Eliassen Group; Hagåtña (GU); Remote; USD 243,560,000 - 272,214,000; Full time

Benefits offered by this job

Medical, Dental, Vision

401k with company matching

Life insurance

Job summary

Eliassen Group is seeking a Principal Data Scientist to scale data science and AI capabilities for end-to-end payment optimization. You will work with ML engineers and product partners to design and deploy real-time models and intelligent decision engines.

The role blends strategic leadership with hands-on contributions across architecture, code reviews, and production-grade ML solutions, mentoring senior data scientists and guiding roadmaps.

Qualifications

• 7+ years in ML research or engineering.
• 5+ years building large-scale real-time ML systems in production.
• Proficiency in Python (Pandas, NumPy, scikit-learn) and strong SQL experience.
• Experience leading solution design and translating business requirements into tech solutions.
• Excellent communication with technical and business audiences, including executives.

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 with rapid experimentation.
• Oversee and contribute to ML model development, deployment, validation, and maintenance.
• Establish best practices for ML modeling and adopt modern tools and infrastructure.
• Mentor a senior data science team and collaborate with product, engineering, data, and compliance teams.

Skills

ML leadership

Python

SQL

Real-time ML

Communication

Education

Bachelor's or Master's in CS/Stats/Math/Engineering; PhD preferred

Tools

AWS

GCP

Snowflake

Databricks

Vertex AI

Job description

Eliassen Group is seeking a Principal Data Scientist to scale data science and AI capabilities for end-to-end payment optimization. You will work with ML engineers and product partners to design and deploy real-time models and intelligent decision engines.

The role blends strategic leadership with hands-on contributions across architecture, code reviews, and production-grade ML solutions, mentoring senior data scientists and guiding roadmaps.