Senior Data Scientist - Payments

Plaid2 weeks ago

Location

San Francisco

Type

Full Time

Salary

USD 180,000 – 250,000

Level

Senior

Role

Data Scientist

Posted

Feb 28, 2026

Full TimeSenior

The role

Summary

Plaid is seeking a Senior Data Scientist to drive impactful data insights and machine learning solutions in the payments ecosystem, focusing on improving financial products through advanced analytics and innovative data-driven approaches.

What you'll do

Data Analysis: Apply quantitative analysis and data mining techniques to generate insights for API product improvements

Experimental Design: Conduct large-scale A/B experiments and analyze results to drive product decisions

Machine Learning Innovation: Identify and develop machine learning signals and models to enhance financial product capabilities

Cross-Functional Collaboration: Inform and influence product and engineering teams through data-driven presentations and insights

Strategic Planning: Develop long-term data science roadmaps and champion a data-first approach across the organization

What we look for

Technical

Programming SkillsProficient in Python for exploratory data analysis and independent coding

Data ToolsDeep expertise in SQL and data visualization tools

Cloud TechnologiesFamiliarity with AWS cloud stack and data infrastructure

Education

Academic BackgroundBachelor's degree in Computer Science, Statistics, Engineering, Economics, or related field

Experience

Industry Experience5+ years in a product-focused Data Science role

Skills

Required skills

Machine Learning TechniquesAdvanced knowledge of classification, clustering, optimization, deep neural networks, and NLP

Experimental AnalysisAbility to conduct and interpret large-scale A/B experiments

Cross-Functional CommunicationStrong ability to translate complex data insights for diverse teams

Nice to have

Data Pipeline ToolsExperience with DBT or Airflow for data pipeline development

Compensation & benefits

Salary

USD 180,000 – 250,000 (annual)

Stock options

Available

Benefits

Diversity and Inclusion

Committed to building a diverse and inclusive workplace that values unique perspectives

Equal Opportunity

Non-discriminatory hiring practices that welcome candidates from all backgrounds

Interview process

1
Initial Screening — Resume review and initial phone/video consultation
2
Technical Assessment — Data science skills evaluation and problem-solving challenge
3
Onsite/Virtual Interviews — Multiple rounds with data science, product, and team members
4
Final Interview — Discussion with senior leadership and final evaluation