Senior Data Scientist, Payments & Fraud (Hybrid)

Possible Financial Inc.; Seattle (WA); Hybrid; USD 176,000 - 191,000; Full time

Benefits offered by this job

Stock options

Full benefits

Bonus plan

Commuter benefits

Office with free drinks and food

Job summary

Possible Finance is seeking a Senior Data Scientist to own the data science behind how money moves, building the payments-health scorecard and monitoring to surface anomalies. You will time payments, design retry strategies, and tackle payments fraud with recurring reporting and risk models.

You will work with Python, SQL, and PySpark on Databricks, with Datadog for monitoring, partnering with Engineering, Product, and Risk to shape the payment strategy.

Qualifications

• Depth in data science fundamentals and payments domain knowledge.
• Experience with modeling, production monitoring, and experiment design.
• In-depth understanding of payment rails (ACH, RTP, card) and payment behavior.
• Hands-on production ML development: model deployment, drift monitoring, retraining.
• Strong Python and SQL, large datasets in PySpark on Databricks.
• Experimentation and causal inference skills; ability to choose appropriate methods.
• Feature engineering instincts for transactional data.

Responsibilities

• Own the data science behind how money moves at Possible.
• Define and build the payments-health scorecard and monitoring for anomalies.
• Design retry strategies that align with customers' pay cycles to improve first-pass payments.
• Develop models and reporting to understand payments fraud and risk of new methods.
• Collaborate with Engineering, Product, and Risk to inform the engineering roadmap.

Skills

Python

SQL

PySpark

Databricks

MLflow

XGBoost

Datadog

Experimentation

Causal inference

Feature engineering

Production ML

Payments domain

Observability tooling

Tools

Databricks

Datadog

MLflow

XGBoost

Python

SQL

Job description

Possible Finance is seeking a Senior Data Scientist to own the data science behind how money moves, building the payments-health scorecard and monitoring to surface anomalies. You will time payments, design retry strategies, and tackle payments fraud with recurring reporting and risk models.

You will work with Python, SQL, and PySpark on Databricks, with Datadog for monitoring, partnering with Engineering, Product, and Risk to shape the payment strategy.