Octane is a Fintech company whose mission is to connect people with their passions. The transaction process for large purchases such as powersports, RVs, boats, and home improvements is slow and frustrating, but Octane is changing that through automated underwriting, innovative credit products, and financing through our in-house lender Roadrunner Financial. Octane reaches millions of enthusiasts through editorial brands like Cycle World and Cycle Volta and helps consumers buy their favorite products with instant, frictionless financing on Octane.co. Octane is revolutionizing lending in under-served verticals that account for tens of billions of dollars in annual transactions.

Octane is gaining traction quickly with customers, as evidenced by growth in originations through our platform of more than 2X year-over-year. Octane works with more than 3,500 merchants in the USA and offers promotional financing with low rates for 40 OEM brands. Because we’re the platform and the lender, we have both high growth and positive unit economics - rare for a fintech. We have raised more than $139M in venture capital from leading investors such as IA Ventures, Valar Ventures, and Contour Venture Partners, and our lending securities are rated AA by S&P.

We are seeking a talented data scientist to lead and execute projects related to credit risk analytics and model development, working at all phases of the data science lifecycle. You will be collaborating with a versatile team of data scientists and financial professionals to design and implement models underlying the core functions of Octane’s lending business and loan portfolios.

Responsibilities:

• Analyze large data sets of proprietary and third-party data to derive insights and recommendations for policy and strategy decisions, 
• Perform detailed analysis and interpret information to make recommendations to senior management on critical strategies. Communicate and present results of analyses and recommendations to high-level stakeholders
• Design and conduct customer-facing experiments that improve our user experience and grow loan originations
• Design and monitor key credit KPIs to provide insights into the credit lifecycle
• Use data analytics to optimize strategies to underwrite consumer loan programs within risk and business constraints, find sources of incremental yield, mitigate excess risk, and optimize for value
• Forecast loss and performance under varied credit and economic conditions 
• Build dashboards to provide business insights and drive risk strategy decisions
• Champion data analytics and help advance our culture of data-driven decision-making

Requirements:

• Excellent Python and SQL skills
• Strong data manipulation and exploratory data analysis skills
• A track record of taking initiative and driving results, and a passion to build, design and transform a young organization
• Strong communication skills and experience working across teams
• MS degree, ideally in a quantitative field such as applied math, statistics, econometrics, or engineering, or 3+ years of experience in a data-related field
• Industry experience within Financial Services, Consumer Credit, FinTech, or similar preferred
• Knowledge of various data techniques including descriptive analytics, hypothesis testing, probability, optimization, classification, etc.

Benefits

• Robust Health Care Plans (Medical, Dental & Vision)
• Up to 5 weeks PTO (self-managed)
• Generous Parental Leave
• Retirement Plan (401k) with Company contribution 
• Educational Assistance/Tuition Reimbursement up to $3K/year 
• Powersports Safety Benefit: reimbursement of up to $500/year for the purchase of any powersports safety equipment
• Life Insurance (Basic, Voluntary & AD&D)
• Short Term / Long Term Disability & Life insurance
• Team Activities (remotely)
• Monthly company gift

Octane Lending is an equal opportunity employer committed to providing equal employment opportunity without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, or any other protected status with respect to recruitment, hiring, promotion and other terms and conditions of employment.

#LI-JL1

#LI-Hybrid