JobsEnova

Senior Data Scientist - Marketing (Hybrid)

Enova · Chicago, IL · Marketing

Posted Sep 11, 2026 · We last checked this listing on Sep 20, 2026

Apply at Enova

Likely interview questions for this role

Written from this job description, not a generic list. Each one notes what the interviewer is really checking.

Behavioral

Tell me about a time your value or LTV model disagreed with what another team's model said the customer was worth. How did you resolve it?

ability to reconcile competing analytical frameworks and collaborate rather than just defend their own model

Tell me about a time you had to explain a modeling decision to people who weren't technical, and it actually changed what they decided to do.

communication skill and whether their analysis actually drove business action, not just got shared

Describe a situation where you had to work independently on an ambiguous problem with no clear playbook. How did you decide where to start?

self-direction and structured problem-solving in a fast-paced, loosely defined environment

Tell me about a model you built that got deployed and then had to be maintained over time. What broke, and how did you find out?

experience with the full model lifecycle including monitoring and maintenance, not just building and handing off

Technical

Walk me through how you would build a model that predicts customer lifetime value at the moment someone just clicks an ad, before we know almost anything about them.

whether the candidate understands early-funnel modeling with sparse features and can reason about signal availability at different funnel stages

Say you've got a value prediction ready to send to Google Ads through an offline conversion upload. Tell me how that pipeline actually works end to end and what could go wrong with latency or data quality along the way.

hands-on knowledge of conversion APIs and offline upload mechanics, and whether they think operationally about reliability, not just modeling

How would you design an experiment to prove that value-based bidding actually improved acquisition efficiency, not just shifted which customers we happened to acquire that month?

depth in causal inference and incrementality testing versus just correlational before/after comparisons

How do you think about the tradeoff between a model that's more accurate but slower to update, versus one that's simpler and can react to fresh data faster, when it's directly driving ad spend?

understanding of the real-time constraints unique to feeding bidding algorithms versus offline analytics

What's your experience with SQL and Python for pulling together marketing and financial data that lives in different systems, and can you describe a messy data integration you've had to solve?

concrete technical fluency and comfort with real-world data plumbing, not just clean datasets

How would you approach allocating budget across paid search, paid social, and other channels when each platform reports success differently and attribution isn't perfectly clean?

grasp of cross-channel measurement challenges and skepticism toward platform-reported numbers

Situational

Suppose the Pricing and Profitability team updates their core LTV model and the assumptions shift. Your bidding models are already live and spending real budget. What do you do first?

judgment about production risk, versioning, and how they'd manage dependency on another team's evolving model

If Meta's bidding algorithm started spending disproportionately on leads with high predicted value but the actual downstream conversion or repayment didn't match, how would you investigate whether the problem is your model, their platform, or something else?

diagnostic thinking and comfort separating model error from platform behavior and external noise

If leadership asked you to justify shifting spend away from a channel that looks efficient on last-click conversions but you suspect is bringing in low lifetime value customers, how would you make that case with data?

ability to translate the core value-based bidding argument into a persuasive, evidence-backed business recommendation

Practice this interview out loud.

Offer builds a real interview for this exact role at Enova from your resume and this job description, asks the questions one at a time, and tells you what landed. The first one is free.

Practice this out loud

The full job description

As published by Enova.

<p><em>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.</em></p> <p><strong>About the role:</strong></p> <p>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.</p> <p>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.</p> <p>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 &amp; Profitability team, whose lifetime value and profitability models form the analytical foundation your bidding models will build on.</p> <p>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.</p> <p>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.</p> <p><strong>Key responsibilities:</strong></p> <ul> <li>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</li> <li>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</li> <li>Partner with the Pricing &amp; Profitability team to ensure your value estimates stay consistent with Enova's core lifetime value and return-on-equity models as they evolve</li> <li>Design and analyze experiments (holdouts, geo tests, incrementality studies) that measure whether value-based bidding actually improves acquisition efficiency and portfolio quality</li> <li>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</li> <li>Communicate insights and recommendations to Marketing and Data Science leadership, providing a data-driven perspective on where and how we grow</li> </ul> <p><strong>Requirements:</strong></p> <ul> <li>Degree in Data Science, Statistics, Mathematics, Economics, Computer Science, or a related field</li> <li>4+ years of experience in Data Science, Analytics, or a related field</li> <li>Proficient programming skills with Python and the ability to write customized programs for meaningful data analysis</li> <li>Experience working with relational databases, such as SQL</li> <li>Excellent knowledge of applied statistical methods and machine learning models</li> <li>Strong problem-solving skills and the ability to work independently in a fast-paced, dynamic environment</li> </ul> <p><strong>Preferred (but not required — we'll teach you):</strong></p> <ul> <li>Exposure to digital marketing or martech/adtech: paid search or paid social platforms, conversion tracking, attribution, or marketing measurement</li> <li>Experience in finance or lending, lifetime value estimation, or unit economics modeling</li> <li>Experience deploying models into production systems or building automated data pipelines</li> </ul> <p><strong>Compensation:</strong></p> <p>The budgeted annual salary range for this position is<strong>&nbsp;</strong>$96,000 to $125,000<strong>.</strong>&nbsp;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&nbsp;<a href="https://www.enova.com/culture/#:~:text=Full%2Dtime%20employees%20receive%20medical,and%20dependent%20daycare%3B%20and%20more!">here</a>.</p><div class="content-conclusion"><p><strong>Benefits &amp; Perks:</strong></p> <ul> <li>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.</li> <li style="font-weight: 400;"><span style="font-weight: 400;">Health, dental, and vision insurance including mental health benefits</span></li> <li style="font-weight: 400;"><span style="font-weight: 400;">401(k) matching plus a roth option (U.S. Based employees only)</span></li> <li style="font-weight: 400;"><span style="font-weight: 400;">PTO &amp; paid holidays off</span></li> <li style="font-weight: 400;"><span style="font-weight: 400;">Sabbatical program (for eligible roles)</span></li> <li style="font-weight: 400;"><span style="font-weight: 400;">Summer hours (for eligible roles)</span></li> <li style="font-weight: 400;"><span style="font-weight: 400;">Paid parental leave</span></li> <li style="font-weight: 400;"><span style="font-weight: 400;">DEI groups (B.L.A.C.K. @ Enova, HOLA @ Enova, Women @ Enova, Pride @ Enova, South Asians @ Enova, APEX @ Enova, and Parents @ Enova)</span></li> <li style="font-weight: 400;"><span style="font-weight: 400;">Employee recognition and rewards program</span></li> <li style="font-weight: 400;"><span style="font-weight: 400;">Charitable matching and a paid volunteer day…Plus so much more!</span></li> </ul> <p><strong>About Enova</strong></p> <p><span style="font-weight: 400;">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.</span><span style="font-weight: 400;">&nbsp;</span></p> <p><span style="font-weight: 400;">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 </span><a href="http://www.enova.com/culture"><span style="font-weight: 400;">here</span></a><span style="font-weight: 400;">.&nbsp;</span></p> <p><span style="font-weight: 400;">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</span><a href="https://www.enova.com/ccpa/"><span style="font-weight: 400;"> </span><span style="font-weight: 400;">here</span></a><span style="font-weight: 400;"> to review our California Privacy Policy for Job Applicants.</span></p></div>

Apply at Enova

Related jobs

Salesforce Team Lead (Hybrid)

Enova · Chicago, IL

Posted Sep 18 · Verified Sep 20

Internal Communications Lead (Hybrid)

Enova · Chicago, IL

Posted Sep 17 · Verified Sep 20

Contact Center Supervisor - Collections (Hybrid)

Enova · Chicago, IL

Posted Sep 16 · Verified Sep 20

Contact Center Supervisor - Loan Application Support (Hybrid)

Enova · Chicago, IL

Posted Sep 16 · Verified Sep 20

NetCredit Loan Processing Representative (Remote)

Enova · Chicago, IL

Posted Sep 9 · Verified Sep 20

Lead Data Scientist - Fraud (Hybrid)

Enova · Chicago, IL

Posted Sep 9 · Verified Sep 20