Octane® is revolutionizing recreational purchases by delivering a seamless, end-to-end digital buying experience. We connect people with their passions by combining cutting-edge technology and innovative risk strategies to make lifestyle purchases - like powersports vehicles, RVs, and OPE - fast, easy, and accessible.

Octane adds value throughout the customer journey: inspiring enthusiasts with our editorial brands, including Cycle World® and UTV Driver®, instantly prequalifying consumers for financing online, routing customers to dealerships for an easy closing, and supporting customers throughout their loan with superior loan servicing.

Founded in 2014, we’re a remote-first company with 550+ employees and over 30 OEM and 4,000 dealer partners.

We are looking for a talented Staff Data Scientist to lead projects related to direct to consumer lead generation models, credit risk analytics, fraud detection, identity verification, collections and servicing model development. You will be working 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. You will touch all phases of the data science lifecycle from working closely with business stakeholders to understand how data science and predictive models can help achieve core business goals and objectives, to then identifying and aggregating appropriate data assets from which to develop relevant predictive machine learning models to deploying, assessing, and monitoring said models.

Responsibilities

Apply state of the art machine learning, statistical modeling, and optimization techniques to drive business value.
Own the entire model development lifecycle from conception to deployment and model updates.
Convert insights into concrete, significant recommendations for business or product improvement, and succinctly communicate these findings to both executive and non-executive partners.
Analyze large data sets of proprietary and third-party data to derive insights and recommendations for policy, strategy, or product decisions.
Research and keep up to date with new modeling techniques and tools.
Mentor and guide junior data scientists, establish best practices for development, measurement and tracking of algorithm performance.

Requirements

7+ years in a data science role (or PhD in a quantitative field with 3+ years as a senior data science or comparable role).
High Fluency with SQL, SparkSQL Python, PySpark and statistical / ML packages.
Experience with AWS or other cloud computing environments, specifically within the data domain.
Experience with Git for code management.
Specific experience deploying machine learning models to production environments and the relevant experience working closely with Product, Data Engineering and Engineering Team members.

Preferred

Experience with Data Bricks.
Experience developing automated feature store data pipelines.
Experience with credit risk models, fraud models, identity verification models, collections models or domain knowledge in financial space as it relates to data science and predictive model development.
Has initiated and driven projects to completion with minimal guidance.
Possesses ability to critically think and prioritize needs of the business.

Compensation: The role described above offers a base salary of $140,000 to $170,000. Your offer will be based on the alignment of your qualifications with the requirements of the job and internal equity. In addition to the above-mentioned salary, Total Rewards include a stock option package, and benefits as outlined below.

Benefits:

Robust Health Care Plans (Medical, Dental & Vision)
Generous Parental Leave
Up to 5 weeks time off (self-managed)
Retirement Plan (401k) with company match!
Educational Assistance/Tuition Reimbursement up to $3K/year
Life Insurance (Basic, Voluntary & AD&D)
Short Term / Long Term Disability
Robust Ancillary benefits including accident insurance, hospital insurance, etc