Credit Risk Analyst

Your role in our mission

As the first peer-to-peer lending marketplace in the states, Prosper has a history of innovation. As a growth company that generates cash, Prosper also has a history of generating results. We are looking for team members that share our passion for applied analysis and who would be excited to be part of a mission‑driven team.

The successful candidate will join Prosper’s Credit Risk team. The Credit Risk team uses analytics tools to develop strategies that govern automated decisions in Prosper’s online marketplace. A Senior Credit Risk Analyst at Prosper has the opportunity to utilize advanced analytical skills to develop verification and fraud strategies using models and data in order to manage credit decisions. An ideal candidate should have strong hands‑on analytical skills and a passion for solving problems in innovative and effective ways.

The faster and more agile risk strategies keep our marketplace competitive and ensure that we continue to deliver on our mission of advancing financial well‑being.

• Develop credit and fraud strategies to improve the credit performance by using data, machine learning models and advanced analytics tools to optimize risk decisions
• Bring innovative/out of the box thinking to make recommendations and to approaching/solving problems
• Design A/B tests and understand the risk and customer experience trade‑offs
• Continue to innovate by testing new data, analytics approaches and models
• Partner with Data Science, Product, Engineering and other partner teams to implement credit and fraud prevention strategies, test and validate pre and post performance
• Conduct ad‑hoc analysis related to risk management, product, and operations
• Analyze portfolio performance at a granular segment level on an ongoing basis.
• Identify trends and conduct root‑cause analysis to isolate key performance drivers.
• Communicate findings and recommendations to the Risk Management and broader Prosper community

• Bachelors degree in Business, Statistics, Mathematics, Computer Science, Engineering or Economics.
• 2+ years of experience with a Bachelors (or less with Masters) managing credit risk and/or fraud and/or data science in consumer lending industry, consumer personal loan / credit card experience is a plus
• Strong analytical and problem‑solving skills
• Must have strong proficiency in SQL and Python, Experience with DBT and Looker will be a plus.
• Strong communication skills – ability to communicate technical subject matter clearly and succinctly to other team members and Senior Management team
• Knowledge and experience of segmentation, statistical procedures, and financial analytic tools are required
• Curious to ask questions, probe into reasons and challenge the status quo
• Strong ownership and motivation to drive business result
• Ability to work in fast‑paced environment and meet deadlines without sacrificing quality
• We will also consider candidates who don’t have financial services experience but have strong technology background and analytical skills
• Self‑starter; comfort dealing with ambiguity

• A connected experience:
  We prioritize high‑touch collaboration and flexibility. Whether you are working from our San Francisco or Phoenix offices or joining us as a fully remote team member, we provide the digital‑first tools and intentional culture to keep you synced and supported.
• Invested in your future: A competitive salary and a 401(k) with a 5% company match to help you build long‑term financial security.
• Holistic well‑being:
  We provide the resources you need to thrive, from flexible time off and paid parental leave to an annual wellness allowance and comprehensive health coverage.
• Professional & personal growth:
  Take advantage of a suite of premium perks, including Udemy access, childcare assistance, pet insurance, and a bevy of additional savings through Beneplace.

122, USD a year

Compensation details:
The salary for this position is $122k - $140k annually, plus bonus and generous benefits. In determining your salary, we will consider your location, experience, and other job‑related factors.

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