Senior Data Scientist - Payments ML, Real-Time Risk, Remote

DEUNA; New York (NY); Remote; USD 150,000 - 210,000; Full time

Benefits offered by this job

Vacations and PTO

Remote work from anywhere

Stock options

Career growth

Job summary

DEUNA is seeking a hands-on data science leader to own machine learning and experimentation for our payments platform. You will design, train, and validate models to increase conversion, reduce declines, and lower fraud in real-time payment flows, collaborating with data engineering and BI teams.

This role offers potential for people leadership as the team grows. You will work in a fast-paced, remote-friendly environment and help establish the data science practice across the organization,

Qualifications

• 5+ years of experience applying machine learning to production problems, preferably in payments/fintech.
• Hands-on depth in feature generation, model selection, training, and hyperparameter tuning.
• Experience designing and running experiments (A/B testing) and proving model impact.
• Proficient in Python and SQL; comfortable querying large datasets.
• Familiarity with Snowflake; knowledge of deployment and ML pipelines.

Responsibilities

• Own end-to-end modeling lifecycle for payment optimization use cases.
• Build and maintain the experimentation framework to measure model performance and impact.
• Collaborate with data teams to surface data-driven insights and improve ML infrastructure.

Skills

Machine learning

Python

SQL

Experimentation

A/B testing

Feature engineering

Snowflake

TensorFlow

Airflow

Communication

Tools

Snowflake

TensorFlow

Airflow

SQL

Job description

DEUNA is seeking a hands-on data science leader to own machine learning and experimentation for our payments platform. You will design, train, and validate models to increase conversion, reduce declines, and lower fraud in real-time payment flows, collaborating with data engineering and BI teams.

This role offers potential for people leadership as the team grows. You will work in a fast-paced, remote-friendly environment and help establish the data science practice across the organization,