Analytics & Risk Strategy
New York, NY /
Who We Are:
Ocrolus is a fintech infrastructure company that transforms documents into actionable data. Powered by Artificial Intelligence and a unique human-in-the-loop data validation process, Ocrolus plugs directly into customer workflows via API, eliminating the need for manual data work. The solution includes built-in fraud detection and analytics, enabling customers to make smarter and faster business decisions with unprecedented precision.
Use-cases include loan underwriting, account openings, invoice processing, and other document-intensive processes. Ocrolus has raised over $30 million in venture capital, backed by Oak HC/FT, FinTech Collective, Bullpen Capital, and QED Investors, among others.
You combine analytics and action, equally comfortable diving into a new dataset, educating prospects on our analytical capabilities, or discussing end-to-end risk management strategies with clients. You will drive growth and adoption in the Ocrolus Analytics business by developing positive-sum partnerships, formulating winning go-to-market strategies, and engaging with clients and prospects on analytical use cases. Along with partners across the business, you will develop high-impact analytical solutions that Ocrolus is uniquely positioned to provide and help bring them to market.
- Foster a strong partnership with revenue teams on prospecting, solution development, and client upsell for analytics and data products.
- Increase adoption, usage, and retention of analytics among clients
- Conduct high-quality analysis and present compelling findings to engage clients in the development of Ocrolus products
- Develop partnerships with best-in-class data providers that augment our ability to deliver analytical value
- Create solid go-to-market strategy and execution for each new analytical product, release, and partnership
- Enhance client understanding of analytical offering and roadmap
- Work with clients to advocate best practices for advanced risk management and fraud management methodologies
- 7+ years of working experience
- Experience in analysis of consumer and/or business credit risk - likely at a bank, fintech, or consulting company
- Familiarity with financial technology ecosystem - particularly data sources and decision systems
- Knowledge of the development and use of credit decisioning models (even though you may not be a data scientist yourself)
- Keen understanding of the lending risk management lifecycle, including the data and decisions made in underwriting, pricing, line assignment, and customer management
- Experience analyzing data and assembling raw information into coherent and actionable insights
- Excellent communication skills, both spoken and written. Ability to convey complex topics to a variety of audiences in a compelling way.
- Proficiency in SQL, preferably some experience in Python and/or R
- Experience in developing and executing go-to-market plans for a B2B product, preferably in financial services
- Ability to work in a highly cross-functional manner, including with revenue teams, engineering, data science, and marketing
- Skilled in aggressive listening, ability to ask open-ended questions and synthesize and summarize information
We’re a young and rapidly growing FinTech company - if you have ever wanted to jump on a rocket ship as it’s taking off, now is your chance!