Senior Data Science Leader — AI, ML & Risk

Mariner Finance; White Marsh (MD); On-site; USD 155,000 - 195,000; Full time

Benefits offered by this job

Benefits package

Job summary

Mariner Finance seeks a principal-level data science leader to develop, evaluate, and scale AI/ML solutions across credit risk, collections, loss mitigation, and pricing. You will own end-to-end modeling initiatives from problem framing to production, partnering with risk, technology, and data teams to drive measurable portfolio improvements.

In this role you will mentor junior scientists, define modeling standards, and apply advanced techniques—gradient boosting, transformers, causal

Qualifications

• Bachelor’s degree in a quantitative field; 7+ years data science/statistical modeling experience
• 7+ years leading modeling initiatives through full lifecycle
• Proficiency in Python and SQL; cloud-based modeling in AWS
• Experience with Databricks or similar platforms; strong governance mindset

Responsibilities

• Lead development, evaluation, and deployment of complex ML/AI models for credit risk, collections, loss mitigation, and pricing
• Own end-to-end modeling lifecycle from problem framing to production monitoring
• Provide technical direction, peer review, and coaching to data scientists
• Establish modeling standards, evaluation frameworks, and reusable patterns
• Partner with Risk, Technology, Data to implement scalable solutions in production

Skills

Python

SQL

ML

Databricks

AWS

Risk Modeling

Education

Bachelor’s degree in Data Science, Statistics, Mathematics, Computer Science, Economics, or related field

Tools

Databricks

AWS

Git

Job description

Mariner Finance seeks a principal-level data science leader to develop, evaluate, and scale AI/ML solutions across credit risk, collections, loss mitigation, and pricing. You will own end-to-end modeling initiatives from problem framing to production, partnering with risk, technology, and data teams to drive measurable portfolio improvements.

In this role you will mentor junior scientists, define modeling standards, and apply advanced techniques—gradient boosting, transformers, causal