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# Sr. Data Scientist - BMW Bank

- **Company:** BMW
- **Location:** Salt Lake City, UT, United States
- **Experience:** Expert
- **Salary:** $78,000.0 - $122,000.0
- **Contract:** Permanent contract
- **Skills:** Agile Methodology, Artificial Neural Networks, Big Data, Computer Programming, Data Validation, Data Cleansing, Data Discovery, Data Governance, Extract Transform Load (ETL), Data Presentation, Data Warehousing, Database Queries, R (Programming Language), Apache Hadoop, Python (Programming Language), PostgreSQL, Logistic Regression, Machine Learning, Microsoft SQL Server, Tensorflow, Standard Sql, SAS (Software), Server Administration, SQL Databases, Support Vector Machine, Tableau (Software), Pytorch, Random Forest, Apache Spark, Scikit Learn, Information Technology, Collibra, Data Analytics, Qlikview, Tools for Reporting, Sas Visual Analytics, Alteryx
- **Published:** October 31, 2026
- **Apply:** https://www.jobmonkeyjobs.com/career/28150515/Sr-Data-Scientist-Bmw-Bank-Utah-Salt-Lake-City-7451

## About the Role

* Bachelor's degree (or equivalent experience); quantitative fields preferred (Data Analytics, Statistics, Math, CS, Economics) and quantitative-oriented Master's degree preferred.
 * Minimum 2 years' professional experience as a data scientist or similar in a corporate environment.
 * Proficiency in statistical/model development and machine learning (e.g., linear/logistic regression, random forest, SVM, neural nets) and experience building/deploying ML solutions.
 * Strong programming and data tools experience (SAS, Python, R) and familiarity with ML libraries/frameworks (TensorFlow, PyTorch).
 * SQL expertise for complex queries (preferably MS SQL or PostgreSQL) and experience with data warehouse concepts (star schema/Kimball).
 * Experience with BI/reporting tools and dashboard development (e.g., Tableau, Qlik) and data preparation tools (Tableau Prep, Alteryx).
 * Advanced SAS and SQL programming skills plus experience manipulating large datasets and validating data from multiple sources.
 + Preferences
 + 3+ years' experience at a US federally regulated financial institution with knowledge of credit risk and model risk management regulations.
 + 2+ years' experience in Financial Services or Automotive industry.
 + Experience with Data Governance tools/processes (e.g., Informatica EDC), ETL architecture, Hadoop and Apache Spark.
 + 2+ years participating on project teams using Agile or Waterfall methodologies.
 + 3-5 years of IT experience, and/or certifications such as Lean Six Sigma Black Belt or PMP.
 + Experience with SAS Visual Analytics, Tableau, and SAS installation/administration., As part of the hiring process, you may be required to successfully pass a background check. A satisfactory completion of a background investigation including verification of education, prior employment, criminal history, credit check history, and pre-employment drug screen to the extent permissible under applicable state law, is a condition of your offer of employment and your continued employment. The results of your background investigation are satisfactory and acceptable in the sole judgement and discretion of BMW Shared Services, LLC.

## Description

* Lead data discovery, preparation, and cleansing across multiple structured and unstructured sources to produce high-quality datasets for analysis.
 * Design, develop and deploy predictive and prescriptive models and algorithms (machine learning/statistical) to solve complex business problems and drive revenue, cost, and risk outcomes.
 * Translate business objectives into data science problems and communicate technical results through clear visualizations and data storytelling for non-technical stakeholders.
 * Collaborate with data engineers, data warehouse teams, product managers, IT, and other analytics teams to ensure model integration, monitoring, and production readiness.
 * Serve as the Bank's subject-matter expert for analytics and SAS: lead SAS projects, support SAS server administration/maintenance, and participate in tool selection and vendor evaluations.
 * Support regulatory, audit, and governance activities by producing reports, responding to data requests, and contributing to Data Governance and model risk practices.
 * Mentor colleagues and drive analytics adoption and innovation (including process improvements, MDLC best practices, and Lean Six Sigma initiatives).