Senior Data Scientist, Predictive Modeling, Credit & Risk

Carvana

Confirmed live 2 days ago High trust

Quick summary

Work type
On-site
Location
Tempe, AZ
Posted
99 days ago
Freshness
Confirmed live 2 days ago

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Salary context

How this pay compares to similar roles

Similar $197k
$149k most similar roles pay here $243k

This listing doesn't post a salary. Most similar roles pay $159,093–$234,187.

Based on 240 similar postings.

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About Carvana

Carvana is an e-commerce platform for buying and selling used cars, offering customers a fully online purchasing experience with home delivery, financing, and vehicle trade-ins through its network of automated car vending machines and inspection centers.

Carvana currently has 51 open roles on FindRole.

Listed pay typically runs $65,000–$76,500 across 10 roles with salary data.

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At a glance

TL;DR · Senior Data Scientist, Predictive Modeling, Credit & Risk

Senior Data Scientist, Predictive Modeling, Credit & Risk joins the Credit & Risk modeling team to develop, validate, and productionize high-impact predictive models that inform risk assessment and decisioning across the business. The role involves improving core credit and risk models through incremental advancements in accuracy and robustness by leveraging structured and unstructured data sources. Key responsibilities include designing, training, and deploying advanced machine learning models such as gradient boosting, representation learning, embeddings, and transformer-based approaches. Candidates must possess 5-8+ years of experience building production models, with proficiency in Python, SQL, LightGBM, and XGBoost. The role requires strong statistical intuition to manage bias/variance tradeoffs while translating complex modeling problems into scalable production systems. This position addresses critical business challenges within the credit, risk, fraud, and underwriting domains by creating reusable patterns for broader organizational use.

What does a Data Scientist earn?

Median $162025 from 276 postings across 61 companies.

See salary data

What you'll do

  • Improve core credit and risk models through incremental advancements in accuracy, robustness, and coverage.
  • Leverage structured and unstructured data sources to drive improvements in model decision quality.
  • Design, train, and deploy advanced machine learning models including gradient boosting and transformer-based approaches.
  • Build and apply rigorous evaluation frameworks like backtests and simulations to guide model iteration.
  • Balance model complexity with business objectives to ensure reliability and maintainability.
  • Partner with data engineering teams to ensure models are production-ready, scalable, and monitorable.
  • Translate successful modeling techniques into reusable patterns and abstractions for other teams.
  • Provide technical leadership through design reviews, code reviews, and informal mentorship.

What we're looking for

  • Bachelor's degree in Computer Science, Statistics, Math, Quantitative Economics, or a similar field from an accredited institution.
  • 5 to 8+ years of experience building and deploying predictive models in production environments.
  • Proven track record of iteratively improving models over time rather than just developing them offline.
  • Proficiency with modern machine learning techniques including LightGBM, XGBoost, neural networks, and representation learning.
  • Strong statistical intuition regarding bias/variance tradeoffs, generalization, and experimental validity.
  • Fluency in Python and SQL with production-quality coding standards.
  • Ability to translate ambiguous modeling problems into successful experiments and production impacts.
  • Experience with embeddings, transformers, or integrating unstructured data like text and images is preferred.

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