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

Free drinks and food at office

Job summary

Possible Finance in Seattle 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 across channels and experiments. You will define how we time payments and design retry strategies that align with our customers’ pay cycles, reducing failed payments and improving recovery.

You will work in Python, SQL, and PySpark on Databricks, with Datadog for monitoring, and collaborate with Engineering,

Qualifications

• Depth in data science fundamentals and payments domain knowledge.
• Hands-on production ML development with model deployment and monitoring.
• Strong Python and SQL and experience with large datasets in PySpark.

Responsibilities

• Owns data science behind how money moves at Possible.
• Defines the payments-health scorecard and monitoring to surface anomalies.
• Designs retry strategies to align payments with customers' pay cycles and reduce failed payments.
• Redefines how payments fraud is understood and develops recurring reporting and risk models.
• Partners with Engineering, Product, and Risk to embed payment strategy in the roadmap.

Skills

Python

SQL

PySpark

Databricks

XGBoost

MLflow

Datadog

Experimentation

Causal inference

Payments rails

Tools

Databricks

Datadog

MLflow

XGBoost

Job description

Possible Finance in Seattle 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 across channels and experiments. You will define how we time payments and design retry strategies that align with our customers’ pay cycles, reducing failed payments and improving recovery.

You will work in Python, SQL, and PySpark on Databricks, with Datadog for monitoring, and collaborate with Engineering,