Senior Data Scientist - Marketing (Hybrid)

We are interested in every qualified candidate who is eligible to work in the United States. However, we are not able to sponsor visas or take over sponsorship at this time.

About the role:

We are looking for a Senior Data Scientist to own value-based bidding (VBB) across our digital marketing channels. This is a rare role that sits at the intersection of machine learning and paid media, where your models will be directly making the decisions that drive the digital marketing spend day-to-day.

Here's the problem you'll own: platforms like Google Ads and Meta will optimize toward whatever signal we give them. Optimize toward clicks or raw conversions, and we acquire the wrong customers efficiently. The alternative is to predict what each prospective customer is actually worth to us over their full lifetime, and feed that value signal back to the platforms so their bidding algorithms spend every dollar optimizing on long-term profitability. Building those value models, and the automated systems that deliver their predictions to our ad platform partners, is the core of this job.

You'll sit within our Marketing team at the center of our digital acquisition strategy, while working as part of Enova's broader data science community. You will collaborate especially closely with our Pricing & Profitability team, whose lifetime value and profitability models form the analytical foundation your bidding models will build on.

Beyond VBB, you'll be the analytical partner to Marketing across all digital channels, helping the team understand what's working, design experiments that prove it, and allocate budget where it earns the best return.

You don't need a marketing background to succeed here. If you're a strong data scientist who wants to see your models directly move spend, volume, and profitability every day, we can teach you the domain.

Key responsibilities:

• Build, validate, and maintain machine learning models that estimate customer lifetime value at early funnel stages (click, lead, application) where value signals are needed for real-time bidding
• Design and implement the automated systems that pass value estimates to ad platforms — offline conversion uploads, conversion APIs, and server-side integrations with partners like Google Ads and Meta — and own their reliability, latency, and data quality
• Partner with the Pricing & Profitability team to ensure your value estimates stay consistent with Enova's core lifetime value and return-on-equity models as they evolve
• Design and analyze experiments (holdouts, geo tests, incrementality studies) that measure whether value-based bidding actually improves acquisition efficiency and portfolio quality
• Act as a data science partner to the broader Marketing team on channel optimization: budget allocation, audience and segmentation strategy, campaign measurement, and funnel analytics across paid search, paid social, and other digital channels
• Communicate insights and recommendations to Marketing and Data Science leadership, providing a data-driven perspective on where and how we grow

Requirements:

• Degree in Data Science, Statistics, Mathematics, Economics, Computer Science, or a related field
• 4+ years of experience in Data Science, Analytics, or a related field
• Proficient programming skills with Python and the ability to write customized programs for meaningful data analysis
• Experience working with relational databases, such as SQL
• Excellent knowledge of applied statistical methods and machine learning models
• Strong problem-solving skills and the ability to work independently in a fast-paced, dynamic environment

Preferred (but not required — we'll teach you):

• Exposure to digital marketing or martech/adtech: paid search or paid social platforms, conversion tracking, attribution, or marketing measurement
• Experience in finance or lending, lifetime value estimation, or unit economics modeling
• Experience deploying models into production systems or building automated data pipelines

Compensation:

The budgeted annual salary range for this position is $96,000 to $125,000. Actual annual salary will be determined based on qualifications, skills, experience, and level assessed during the hiring process and may fall outside of the range shown. Additional compensation for this role may include a bonus. All full-time employees are eligible to participate in Company benefits, described in more detail here.

Benefits & Perks:

• Our hybrid roles require in-office work Tuesday through Thursday, with remote flexibility on Mondays and Fridays. This schedule fosters collaboration, team connection, and strategic planning, enhancing communication and effectiveness to drive results.
• Health, dental, and vision insurance including mental health benefits
• 401(k) matching plus a roth option (U.S. Based employees only)
• PTO & paid holidays off
• Sabbatical program (for eligible roles)
• Summer hours (for eligible roles)
• Paid parental leave
• DEI groups (B.L.A.C.K. @ Enova, HOLA @ Enova, Women @ Enova, Pride @ Enova, South Asians @ Enova, APEX @ Enova, and Parents @ Enova)
• Employee recognition and rewards program
• Charitable matching and a paid volunteer day…Plus so much more!

About Enova

Enova International is a leading financial technology company that provides online financial services through our AI and machine learning-powered Colossus™platform. We serve non-prime consumers and businesses alike, while offering world-class technology and services to traditional banks—in order to create accessible credit for millions. 

Being a values-driven organization is at the core of Enova’s success. We live our values by listening to our customers, challenging assumptions, thinking big, setting high expectations, and hiring and developing the best. Through our values and our commitment to making Enova an awesome place to work, we maintain an environment of inclusion and culture where our employees can thrive. You can learn more about Enova’s values and culture here. 

It is our policy to provide equal employment opportunity for all persons and not discriminate in employment decisions by placing the most qualified person in each job, without regard to any other classification protected by federal, state, or local law. California Applicants: Click here to review our California Privacy Policy for Job Applicants.