Data Scientist, Sr. Analyst / Manager #LI- Remote

Pasadena, California /
Risk – Credit Risk /
Full-Time
Scratch Financial ("Scratchpay") is a financial technology startup based in Los Angeles, California. Our goal is to make difficult financial decisions simple and increase accessibility to fair, affordable, and transparent medical financing. Driven by our award-winning technology, Scratchpay has become the fastest growing financing provider in veterinary care, with our payment plans now offered in over 10,000 practices across the U.S. and Canada–ranging from dental offices to optometry clinics. We’re rapidly launching a new Point-of-Sale payment processing suite to help our providers create a better payments experience for their patients.

If putting compassion first, helping create groundbreaking products and continuously iterating & refining those products sound like you, then we encourage you to apply.


Scratch is seeking to hire a Data Scientist to join our credit risk  team and help revolutionize the way patients and pet owners pay for care. The Credit Risk team makes intelligent data-driven decisions to assess incoming risk and designs data based solutions to optimize portfolio performance. We are rapidly pursuing new data sources, increasing our understanding of our customers, building new predictive models, and implementing analytical insights live - all to help the business grow and help more customers fund the care they and their pets need. 

As a part of the Credit Risk team, you will lead projects that extract value from our unique, proprietary, and fast growing data. You will be responsible for analysis, modeling, and execution of projects that will help drive originations and reduce losses for the portfolio. If you enjoy solving problems with data and technology and want to work in an environment where analytics, product, finance, and operations blend together, this is a fantastic opportunity. 

In this role, you will:

    • Explore internal and external data, and combine disparate sources of information into datasets/features for use in analysis
    • Leverage a broad stack of technologies (Python, SQL, R) to reveal interesting insights hidden within numerical and textual data
    • Navigate ambiguous problems with scientific method to yield actionable insights that impact the business
    • Create models to address credit risk and fraud risk in lending. You will be involved in the whole process of model development and deployment (including root cause analysis, data collection, feature engineering, implementation, and live model monitoring)
    • Respond to ad-hoc credit risk issues across all levels of organization

    • We place a high degree of importance on team dynamics and have a transparent and open organization. We are a team of ambitious people who are passionate about our common goal and our respective areas of responsibility. We deliver fast, iterate continuously, and encourage rapid response to change.

The ideal candidate has:

    • 1-6+ years experience in data science, risk analytics, machine learning
    • Excellent problem-framing, problem solving, and project management skills
    • M.S. or PhD degree in a quantitative field with demonstrated core statistical knowledge
    • Strong programming and data extraction skills (we work with SQL, Python, and R)
    • Experience building predictive models or decision strategies in academic research or previous work (we’d love to hear about them!)
    • Experience with financial services datasets/problems (plus)
    • Strong communication skills through text and speech and able to communicate effectively with technical and non-technical audience
Scratchpay is committed to diversity in its workforce and is proud to be an equal opportunity employer. Scratchpay considers qualified applicants without regard to race, color, religion, creed, gender, national origin, age, disability, veteran status, marital status, pregnancy, sex, gender expression or identity, sexual orientation, citizenship, or any other legally protected class.