Pagaya

Financial Services

PrincipalDataScientist

Tel Aviv, Israel
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Lead candidates.

The Brief

“Principal Data Scientist at Pagaya. Skills: Machine Learning, Data Science, applied statistics. lead strategic research initiatives focusing on our Personal Loans asset class. tackle Pagaya’s most challenging, long-term research questions”

What You'll Achieve.

measurable business impact in a production environment; align long-term research goals with Pagaya’s strategic business roadmap

Industry & Context.

Financial Services
Problems you'll solve

tackle Pagaya’s most challenging, long-term research questions; address fundamental challenges; Design multi-domain Data Science solutions; identifying untapped opportunities; Debate and Commit; Dream Big and Act

What They're Looking For.

Must Have

10+ years of experience in Machine Learning with large-scale tabular data, MSc or PhD in a highly quantitative field (Math, Physics, CS, Stats, or EE), Good applied statistics skills, such as distributions, statistical testing, regression, etc., Deep expertise in the Python Data Science stack and advanced applied statistics

Nice to Have

focusing on predictive modeling (Advantage), A track record of translating complex, long-term research projects into significant, measurable business impact in a production environment

What You'll Do.

lead strategic research initiatives focusing on our Personal Loans asset class

tackle Pagaya’s most challenging

long-term research questions

advance our sophisticated models

providing high-level professional leadership and mentorship to data scientists across the group

setting the standard for scientific rigor and innovation

long-term research initiatives

Develop cutting-edge Machine Learning models and algorithms from scratch

Design multi-domain Data Science solutions for the company’s core mission

identifying untapped opportunities within our vast datasets

advising on methodology

and technical roadblocks

How You'll Work.

Team & Collaboration

mentorship to data scientists across the group; Partner with Product, Engineering, and Finance stakeholders; collaboration

Communication Scope

communicate complex scientific concepts to non-technical stakeholders

Full Job Description

About Pagaya Pagaya is a global technology company making life-changing financial products and services available to more people nationwide, as it reshapes the financial services ecosystem. By using machine learning, a vast data network and a sophisticated AI-driven approach, Pagaya provides comprehensive consumer credit and residential real estate solutions for its partners, their customers, and investors. Its proprietary API and capital solutions integrate into its network of partners to deliver seamless user experiences and greater access to the mainstream economy. Pagaya has offices in New York and Tel Aviv. For more information, visit pagaya.com. About the Role We are looking for a visionary Principal Data Scientist to lead strategic research initiatives focusing on our Personal Loans asset class. In this high-impact, individual contributor role, you will be at the absolute forefront of our research department. You will tackle Pagaya’s most challenging, long-term research questions, working hands-on to advance our sophisticated models while providing high-level professional leadership and mentorship to data scientists across the group. Responsibilities Act as the technical authority and professional lead for the Personal Loans research group, setting the standard for scientific rigor and innovation. Spearhead complex, long-term research initiatives that address fundamental challenges in credit risk, behavioral modeling, and portfolio optimization. Develop cutting-edge Machine Learning models and algorithms from scratch, moving from high-level hypothesis to production-ready solutions. Design multi-domain Data Science solutions for the company’s core mission, identifying untapped opportunities within our vast datasets. Mentor senior and staff data scientists, advising on methodology, experimental design, and technical roadblocks without the overhead of people management. Partner with Product, Engineering, and Finance stakeholders to align long-term research goals

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