Senior Data Scientist, Credit Product Analytics

Plaid; New York (NY); On-site; USD 140,000 - 210,000; Full time

Job summary

Plaid is seeking a Senior Data Scientist for the Network Value (Credit) team in New York. You will partner with product managers, engineers, and stakeholders to drive data-informed strategy, build dashboards, and shape credit product features that expand Plaid's consumer network.

You will translate business questions into analytics projects, create actionable metrics, and run experiments to guide product decisions. Expect collaboration across teams and impactful impact on growth and performance.

Qualifications

• 5–8+ years of experience in data science or a related analytics role.
• Experience as a product data scientist for a consumer-facing product.
• Experience with experimentation and strategic insight generation in a product environment.
• Strong SQL skills and experience building metrics for stakeholders.
• Experience working with data pipelines using Airflow and dbt.
• Ability to influence prioritization, roadmaps, and execution.
• Strong communication skills for cross-functional teams.

Responsibilities

• Translate business questions into analytics projects and KPIs.
• Build data models, dashboards, and OKRs tied to business goals.
• Collaborate with product managers and engineers to shape strategy.
• Design experiments to inform feature launches and decisions.
• Maintain scalable analytics reporting with Python, Redshift, Databricks.

Skills

Strong SQL skills

Experimentation

Data storytelling

Data modeling

Cross-functional collaboration

Stakeholder influence

Communication

Product analytics

Tools

Airflow

dbt

Python

Redshift

Databricks

Job description

Plaid is seeking a Senior Data Scientist for the Network Value (Credit) team in New York. You will partner with product managers, engineers, and stakeholders to drive data-informed strategy, build dashboards, and shape credit product features that expand Plaid's consumer network.

You will translate business questions into analytics projects, create actionable metrics, and run experiments to guide product decisions. Expect collaboration across teams and impactful impact on growth and performance.