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Senior Credit Analyst

Remote:

Full Remote

Experience:

Senior (5-10 years)

Work from:

California (USA), United States

Offer summary

Qualifications:

8+ years analytics engineering experience, Experience in credit risk analysis.

Key responsabilities:

Perform credit risk analysis and customer segmentation
Build financial models and dashboards
Support cross-functional teammates in analyses
Create and maintain data transformations
Utilize BI tools for data visualization

Step Financial Services Scaleup https://www.step.com/

51 - 200 Employees

See more Step offers

Job description

Gen Z is the generation of the side hustle. 💪🏻 They’re creators. 👩‍🎤 They’re freelancers. 🧑‍💻 They’re investors. 👩‍💼 And they’re not afraid to take on challenges, especially when it comes to their finances - and we’re here for it.

Step is a next-generation financial services company building a better banking experience to help teens and young adults achieve financial independence and knowledge at an earlier age. We’re on a mission to improve the financial future of the next generation by empowering teens to start their financial journey today. Step is a well-funded Series C company that has raised more than $175M, focused on disrupting the banking industry through a differentiated mobile-first consumer experience.

Teens and families love our product. We eclipsed 1 million customers in just four months after launch and have now crossed 4 million customers. If you’re looking to join a fast-growing company with a strong mission and vision that puts people first, we want to meet you!

The role

We seek an experienced Senior Credit Analyst to enable and accelerate Step’s Lending projects.

What you'll do

Perform credit risk analysis and customer segmentation.
Build financial models to drive lending strategy.
Design and build dashboards to track lending KPIs.
Support all cross-functional teammates for end-to-end analysis on key initiatives.
Perform adhoc analysis to understand business and customer trends.
Design, create and maintain data transformations to produce reusable and efficient datasets for data analytics and data science use cases.
Model, create and maintain data in our self-serve BI tools.