# Every career journey is personal. That's why we empower you with the tools and support to create your own success story. # # Be challenged. Be heard. Be valued. Be you ... be here. Job Summary Under supervision and guidance, the Data Scientist, 2 applies data science in advanced analytics such as predictive modeling and data mining in a big data environment in order to deliver predictive models and insights. The Data Scientist, 2 produces insights that encompass the different product types and channels and maintain regulatory standards. The Data Scientist, 2 assists with ensuring accurate and timely implementation of solutions, quantifying the overall financial impact to the business, and communicating results. Essential Job Functions: - Analytics – under supervision and guidance, completes the following: 1) extracts and samples data, conducts data integrity checks and applicable data pre-processing such as treatment of missing values and outliers 2) conducts exploratory data analysis for preliminary data insights to drive the selection of modeling approach that best addresses the business problem 3) reveals hidden data patterns by data mining using unsupervised learning techniques such as clustering analysis and factor analysis 4) conducts feature engineering to create/derive model predictors with strong predictive power 5) trains/tunes classification/regression models by applying supervised learning techniques such as generalized linear models assuming applicable underlying distributions such as logit and gamma, tree-based models such as decision trees, random forest, boosted trees, etc., and neural net models 6) conducts proper model test/validation, diagnoses and fixes model issues (e.g., over-fitting) when applicable. Sizes the impact of using the models in production as part of the current strategy. Presents results and business case to manager. Provides support for implementation and monitoring of solutions that are implemented. - Collaboration – under supervision and guidance, translates analytical results into useful recommendations for review with manager. Demonstrates strong verbal and written communication skills when working with internal partners and when presenting results to various audiences. Develops foundational knowledge of credit card operations, banking, financial, loyalty rewards, retail, and credit card regulations while working with the business. Collaborates with other data scientists in the company to share best practices and data science innovations. - Data Science innovation – with direction from leader, researches industry trends in data science of new tools, emerging algorithms, advanced platforms, and alternative data to enhance modeling effectiveness and efficiency. Conducts use case testing for new tools/techniques/platforms/data and provides user input/feedback. - Model Risk Management - develops foundational knowledge on common model risks and related regulatory requirements; applies proper 1st line of defense controls during model development process to minimize model risk; creates comprehensive model governance documentation and archives model data, scripts, and results; collaborates with model risk management partners to complete model validation/auditing; completes remediation as required by model governance process. Reports To: Manager or higher Direct Reports: None Working Conditions/ Physical Requirements: - Normal Office Environment. Minimum Qualifications: - Education Required: Bachelor’s Degree in Statistics, Mathematics, Engineering, Data Science, Economics, Computer Science, or another quantitative field - 2 to 5 years of related work experience Preferred Qualifications: - Education: Master’s Degree, PhD in Statistics, Mathematics, Engineering, Data Science, Economics, Computer Science, or another quantitative field - 3 or more years of professional hands-on experience in developing statistical models/machine learning models and conducting data mining to solve business problems. Experience in extracting and processing large files/data sets. Experience interpreting model results and translating insights into business recommendations. - Experience interpreting model results and translating insights into business recommendations. - Strong machine learning fundamentals, statistics and model evaluation. - Knowledge, Skills and Abilities: - Must: - Python - Spark SQL - Statistical Concepts - Structured Query Language (SQL) - Python, SQL - ML algorithms (Bagging, Boosting, Neural Nets) - Databricks & Spark - Git / version control - ML experimentation and evaluation tools - Data visualization and reporting tools - Cloud computing - AWS and/or Azure - Data Analytics - Data Science - Machine Learning - Pivot Tables - PowerPoint Presentations - Predictive Modeling - Good to Have: - Financial Services - Natural Language Processing (NLP) - Time Series Forecasting - Cloud platforms (Azure / AWS / GCP) - ML experimentation and monitoring tools - GenAI tooling (LLM frameworks, embeddings, vector stores) - Advanced Python and SQL for data science and modeling. - Experience with large‑scale data and distributed processing (Databricks / Spark‑like environments). - Experience working with production ML systems. - Working understanding of GenAI fundamentals, including Transformers, LLMs, embeddings, and prompting concepts. - Strong problem‑solving and stakeholder communication skills. - Model monitoring, drift detection, and retraining workflows. - Optimization, interpretability (SHAP, feature importance). - Exposure to GenAI/LLM‑based modeling (use‑case dependent). - Exposure to Agentic AI concepts (tool‑using agents, workflow orchestration). - Familiarity with RAG‑based systems and retrieval strategies. Other Duties This job description is illustrative of the types of duties typically performed by this job. It is not intended to be an exhaustive listing of each and every essential function of the job. Because job content may change from time to time, the Company reserves the right to add and/or delete essential functions from this job at any time. ### About Bread Financial® At Bread Financial, you’ll have the opportunity to grow your career, give back to your community, and be part of our award-winning culture. We’ve been consistently recognized as a best place to work nationally and in many markets and we’re proud to promote an environment where you feel appreciated, accepted, valued, and fulfilled—both personally and professionally. Bread Financial supports the overall wellness of our associates with a diverse suite of benefits and offers boundless opportunities for career development and non-traditional career progression. Bread Financial® (NYSE: BFH) is a tech-forward financial services company that provides simple, personalized payment, lending and saving solutions to millions of U.S. consumers. Our payment solutions deliver growth for some of the most recognized brands in travel & entertainment, health & beauty, technology, electronics, jewelry, home and specialty apparel through our co-brand and private label credit cards and pay-over-time products providing choice and value to our shared customers. Additionally, we offer Bread Financial general purpose credit cards and saving products that empower our customers and their passions for a better life. Bread Financial proudly marks 30 years of success in 2026. To learn more about our global associates, our performance and our sustainability progress, visit [breadfinancial.com](https://www.breadfinancial.com/) or follow us on [Instagram](https://www.instagram.com/breadfinancial) and [LinkedIn](https://www.linkedin.com/company/bread-financial). - All job offers are contingent upon successful completion of credit and background checks. - Bread Financial is an Equal Opportunity Employer. Job Family: Data and Analytics Job Type: Regular ### ###