Data Scientist (FinTech)

TL;DR

Data Scientist (FinTech): Build, maintain, and improve decision systems and predictive models that drive hirify.global’s business impact, with an accent on data mining, machine learning, and rigorous evaluation. Focus on designing and running in-market experiments, prototyping solutions to business problems, and applying advanced analytics methods to real-world customer and financial data.

Location: Remote (continental United States) or in the corporate office in Utah

Company

hirify.global provides in-store and e-commerce lease-to-own solutions and operates in the FinTech space.

What you will do

• Develop and maintain decision systems and predictive models for hirify.global’s competitive advantage.
• Explore new internal and external data sources and use findings to improve model performance.
• Design, implement, and run in-market experiment testing for new algorithms, technologies, and processes.
• Prototype solutions to business problems using cutting-edge technologies.
• Recommend and support strategic changes through rigorous analytics and creative problem solving.
• Identify, evaluate, and implement advanced analytics methods.

Requirements

• 2+ years of experience in data science/analytics.
• Master’s degree in a quantitative/technical field (e.g., math, stats, economics, engineering, physics, computer science).
• Experience with R, Python, machine learning tools, and SQL.
• Proven ability to apply advanced models to real-world problems.
• Ability to craft rigorous research and evaluation design.
• Work location: must be able to work remotely from the continental United States or work from the corporate office in Utah.

Nice to have

• Experience in engineering environments.
• Knowledge of DevOps and Git.
• Track record of agentic AI use and implementation.

Culture & Benefits

• Work-from-home role with option to work from the Utah corporate office.
• Full health benefits (medical, dental, vision, life) and parental leave.
• Company-matched 401k, paid time off, and volunteer hours.
• Tuition reimbursement and necessary equipment/services provided.
• Employee stock purchase program and charitable gift matching.

Hiring process

• Interviews to evaluate analytics/modeling experience and practical problem-solving.
• Discussion of fit for data-driven decision making and experimentation approach.