Kafene is a leading point-of-sale financing partner dedicated to empowering
flexible ownership solutions for underserved customers nationwide. By enabling
our retail partners to offer flexible lease-to-own (LTO) purchase options for
prime and nonprime consumers, Kafene helps merchants grow their customer base,
and meet growing demand for furniture, appliances, electronics, tires and
other durable goods. Utilizing more than 20,000 data inputs in tandem with
cutting-edge AI and machine learning technologies, our platform creates a
best-in-class experience for both merchants and customers. With over $100
million in sales since inception, we are rapidly growing and expect to double
our scale in the next 12 months.
Our team values and celebrates our culture, and we are proudly selected as one
of the Built-In Startups to Watch, Lendit Industry award finalist, and Forbes'
Best Startup Employers.
Credit and risk are fundamental pillars of our business. Our talented team of
8 members plays a pivotal role in enabling our company to offer competitive
approval amounts, rates, and pricing to consumers through the company’s
merchant partners. The team leverages advanced AI and machine learning
approaches in combination with statistics and data analytics. Those insights
and recommendations are shared and implemented through a collaborative
approach with the rest of the team.
In this role, you will be responsible for end to end ownership of our retail
partner risk process. This includes developing complex strategies to predict
consumer risk based on merchant type and other metadata. As merchants mature,
you will be responsible for optimizing our programs to drive increased
approval rates, amounts, and utilization. You will be the primary point of
contact in ensuring that our retail partners are given the most competitive
risk program throughout their lifecycle with the firm, creating not only
systematic treatments but also bespoke programs for our larger partners.
You will oversee a growing team of risk operations personnel, responsible for
day-to-day implementation of the processes you will design as they relate to
merchant underwriting, step-up verification, merchant fraud and other risk
operations processes.
**Impact**
-Be a hands-on player / coach to support important merchant risk initiatives. You will need to leverage multiple and complex data sources such as consumer and commercial bureau information, third party vendor data, internal performance metrics and machine learning models to perform quantitative analyses and decision-tree analyses to produce thoughtful recommendations to support healthy business growth.
-Set and monitor risk appetite. Work with sales and operations to ensure smooth implementation and oversight.
-Oversee merchant underwriting qualitative process to improve merchant experience while maintaining control of merchant risk. Continue to enhance and enable the merchant risk operations team.
-Collaborate with the modeling team to evaluate 3rd party vendors’ data and score products to further improve our models and strategies.
-Track new merchant performance and conduct statistical analyses to define new merchant risk appetite by segment to ensure our profitability.
-Unify internal performance and industry / geographical information to create a single framework from which to segment and implement different approval rates, amounts, pricing, and treatment.
-Conduct statistical analyses to assign new merchants into appropriate segments to ensure optimized treatment aligned with key business goals.
-Develop granular merchant approval rate, approval amount, and step up verification strategies, to effectuate both negative tightening and positive boosting.
-Track merchant engagement level (approval rate/approval amount/conversion/volume) and loss performance using BI tools (Sigma) to ensure healthy portfolio growth.
-Work closely with sales, marketing, and analytics teams to conduct ad hoc analysis to determine individual merchant performance and get alignment over merchant treatment policy.
-Automate merchant health review process and guide analysts to review and finalize the final treatment recommendation by working closely with the sales and operation team.
-Monitor and review merchant fraud. Investigate merchant level fraud cases and employee fraud cases to identify relevant patterns & take preventive actions to mitigate fraud risk.
-Partner with the technology team to ensure timely and quality implementation with diligent test validation. Track the performance to ensure that it meets expectations.
**Requirements**
* Advanced degree in quantitative discipline such as Statistics, Operations Research, Economics, Engineering, Data Science, or other STEM majors. -High level proficiency in Python/R, SQL, SAS or other data mining and analytical tools. Familiarity with any decision tree analysis tool, like Enterprise Miner or knowledge seeker, is a plus.
* Strong communication skills.
* Clear presentation skills.
* A collaborative attitude.
* Experience managing a small operational team.
Kafene focuses on Finance Technology. Their company has offices in New York
City. They have a mid-size team that's between 51-200 employees. To date,
Kafene has raised $32M of funding; their latest round was closed on September
2022.
You can view their website at <http://kafene.com> or find them on
[Twitter](https://twitter.com/leasewithkafene) and
[LinkedIn](https://www.linkedin.com/company/kafene).
