Data Scientist - Remote

Company: Sundayy

Location: Location not specified (Remote)

Type: Full-time

Remote: Yes

Posted: 2026-07-11

About this role

About The Company

Progressive Leasing is a leading provider of in-store and e-commerce lease-to-own solutions, with over 20 years of experience in the FinTech industry. Established as an innovative and customer-centric company, we have grown from a startup to an industry leader by simplifying processes, valuing people, and continuously pushing technological boundaries. As a subsidiary of PROG Holdings (NYSE: PRG), we operate within a diverse portfolio that includes Purchasing Power, a prominent employee purchase program using payroll deduction, and Four, a Buy Now Pay Later (BNPL) platform. Our commitment to innovation and excellence positions us at the forefront of the FinTech landscape, serving millions of customers across the United States.

About The Role

We are currently seeking a highly motivated Data Scientist to join our dynamic team. This is a remote work-from-home position that can be performed from anywhere within the continental United States or at our corporate office in Utah. As a Data Scientist, you will play a pivotal role in leveraging analytics, data mining, machine learning, and software engineering to develop solutions that significantly enhance our business operations. Your primary responsibilities will include building and refining decision systems, predictive models, and business processes to maximize impact. You will gain a profound understanding of our customer behaviors, product offerings, and financial metrics by analyzing complex datasets. This role offers an exciting opportunity to work at the cutting edge of data science in a fast-paced, innovative environment, collaborating with a team of like-minded professionals committed to data-driven decision-making and industry leadership.

Qualifications

  • Minimum of 2+ years of experience in data science or related fields
  • Master’s degree in a quantitative or technical discipline such as Mathematics, Statistics, Economics, Engineering, Physics, or Computer Science
  • Proficiency ...

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