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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Data Scientist - **Company:** Open Lending - **Location:** Irving, TX, United States - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Data Analysis, Microsoft Azure, Big Data, Data Infrastructure, Dataspaces, Python (Programming Language), Logistic Regression, Machine Learning, Power BI, SQL Databases, Tableau (Software), Management of Software Versions, Apache Spark, Pandas, Pyspark, Scikit Learn, Xgboost, Machine Learning Operations, Databricks - **Published:** May 19, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=980979d9074d5784 ## About the Role We are seeking a technically strong, highly accountable Senior Data Scientist to lead the development and oversight of credit risk scorecards used in production decisioning and pricing. In this role, you will build and maintain traditional scorecard approaches and machine learning models, and you will own the end-to-end lifecycle: data exploration, model development, validation, deployment partnership, and ongoing monitoring. The ideal candidate has 5-7+ years of hands-on experience building and deploying credit scorecards at a bank, lender, or auto finance environment, and is comfortable operating within model governance expectations (model risk management, documentation, and fair lending considerations). Experience with Databricks is a plus but not required., * 5-7+ years of experience building, validating, and deploying credit risk scorecards (bank, lender, or auto finance strongly preferred). * Strong proficiency in Python for modeling and production-oriented analytics (pandas/Polars, scikit-learn, XGBoost, etc.). * Experience with scorecard modeling workflows: binning, WOE/IV, variable selection, regularization, calibration, reject inference familiarity, segmentation, and stability analysis. * Proven ability to deploy and monitor models end-to-end, including metrics, dashboards, and automated reporting/alerting. * Working knowledge of fair lending / model governance expectations in credit modeling (documentation, monitoring, change management, and stakeholder communication). * Comfort working with large datasets and SQL-based environments; ability to collaborate on scalable pipelines with engineering/data teams. * Strong written and verbal communication skills-able to explain modeling decisions to technical and non-technical audiences. * Nice to have: Databricks (Spark/PySpark, MLflow), Azure-based data ecosystems, feature store patterns, MLOps experience, Power BI/Tableau. ## Description * Build and enhance credit scorecards for underwriting/pricing and risk management, using approaches including logistic regression, and ML methods such as XGBoost. * Own model monitoring in production, including stability and drift (PSI/CSI), performance (AUC/KS, calibration, segmentation), and outcome tracking across vintages and key cohorts. * Establish and maintain champion/challenger frameworks, thresholds, and alerting to support proactive risk management. * Partner with engineering/product to deploy models and supporting pipelines reliably (feature generation, versioning, reproducibility, and release controls). * Drive model explainability and transparency-produce clear model documentation, rationale, limitations, and operational guidance for internal and external stakeholders. * Support model governance activities: validation support, performance reviews, change control, and audit-ready artifacts aligned to model risk expectations. * Integrate fair lending and responsible AI considerations into modeling workflows (disparate impact monitoring, explainability, documentation, and controls aligned with applicable guidance). * Collaborate with analytics, actuarial, product, and data platform teams to improve data quality, feature availability, and decisioning impact. * Identify emerging risk trends and deliver actionable insights to leadership (portfolio shifts, macro sensitivity, policy/strategy implications). ## Related Videos - [PySpark - Combining Machine Learning & Big Data](https://www.wearedevelopers.com/videos/44-pyspark-combining-machine-learning-big-data) - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [TikTok's Privacy Innovation](https://www.wearedevelopers.com/videos/1036-tiktok-s-privacy-innovation) - [Advanced Typing in TypeScript](https://www.wearedevelopers.com/videos/496-advanced-typing-in-typescript) - [Detecting Money Laundering with AI](https://www.wearedevelopers.com/videos/111-detecting-money-laundering-with-ai) - [Empowering Retail Through Applied Machine Learning](https://www.wearedevelopers.com/videos/976-empowering-retail-through-applied-machine-learning) ## Related Articles - [MLops – Deploying, Maintaining And Evolving Machine Learning Models in Production](https://www.wearedevelopers.com/magazine/115-mlops-deploying-maintaining-and-evolving-machine-learning-models-in-production) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [Data Analyst Salary in the UK](https://www.wearedevelopers.com/magazine/278-data-analyst-salary-in-the-uk) - [Graph and AI Trends 2026: Why Is AI Running but Not Yet Delivering?](https://www.wearedevelopers.com/magazine/680-graph-and-ai-trends-2026-why-is-ai-running-but-not-yet-delivering) - [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk)