Principal Data Scientist

Principal Data Scientist

Locations

Scottsdale, AZ | San Francisco, CA | Chicago, IL | New York, NY

Hybrid work model – 3 days in the office

Visa sponsorship not available

About the Role

We're working with a

leading U.S. financial technology company

trusted by major banks and institutions to power secure, real-time payment solutions and identity verification products used by millions of consumers every day.

This organization operates at the heart of the U.S. financial ecosystem – enabling instant, safe, and reliable transactions while preventing fraud and maintaining trust across the payments network.

They're now looking for an exceptional

Principal Data Scientist

to join their growing Data Science organization. In this senior, highly technical role, you'll lead the design, development, and deployment of advanced machine learning models that power

identity

and

payment

systems across a large-scale, data-rich environment.

You'll be hands-on 70–100% of the time – coding, building, and maintaining models in production – while also providing technical leadership, mentoring, and strategic input to help scale data science capabilities enterprise-wide.

What You'll Do

Design, develop, and deploy

analytically derived models to assess risk and detect / prevent fraud – across Identity and Payments (ACH) domains.

Build end-to-end data pipelines

and storage schemes for complex, high-volume datasets using PySpark, Python, and SQL.

Collaborate cross-functionally

with Product, Engineering, ML Platform, and Analytics teams to bring models into production and continuously improve them.

Drive thought leadership

both internally and externally – influencing analytic strategies, evaluating emerging technologies, and representing the company in industry discussions.

Lead by example

mentor junior data scientists, guide analytic design, and ensure best practices for scalable model development and deployment.

Support multiple projects concurrently , managing timelines, documentation, and technical delivery.

What You Bring

10+ years

of experience in data analytics or data science in data-rich environments.

7+ years

of hands-on programming and model development using

PySpark, Python, and SQL .

2+ years of direct experience in

financial services or fintech .

Proven expertise in

machine learning, predictive modeling, and optimization

– from experimentation to production deployment.

Deep familiarity with

AWS SageMaker

or similar ML platforms.

Experience working with

financial data

and understanding of

banking regulations .

Strong communicator who can explain complex analytical concepts to both technical and non-technical stakeholders.

Bachelor's degree in

Mathematics, Statistics, Computer Science , or a related field (advanced degree strongly preferred).

Preferred Qualifications

Advanced degree (Master's or PhD) in a quantitative field.

Experience with

scikit-learn ,

pandas , and other modern ML libraries.

Proven ability to

scale teams, processes, and model pipelines

within large enterprises.

Why Join

Work with

cutting-edge data at scale.

Collaborate with some of the

brightest minds in data science and machine learning .

Drive innovation at the intersection of

AI, risk management, and financial technology

– shaping how consumers and institutions transact safely every day.

If you're a hands-on data science leader ready to build, deploy, and scale models that impact millions of users daily – we'd love to hear from you.

J-18808-Ljbffr