Top Data & Analytics Jobs in Baltimore, MD

Ensure accuracy, integrity, and compliance of master and reference data across enterprise systems. Enforce governance, validate and remediate Salesforce and other system records, perform audits/cleansing/de-duplication, support migrations and integrations, produce reports and insights, and partner with global teams to improve data processes and adoption of standards.

Analyze large and diverse datasets to uncover insights, develop/train/deploy machine learning models, design data preprocessing pipelines, and create visualizations and reports. Collaborate with cross-functional teams to build predictive models, recommendation systems, and optimization algorithms to drive business improvements.

Lead credit underwriting, pricing, verification, and portfolio performance for personal loans. Use data and ML/AI to design automated decisioning, manage credit/fraud risk, forecast losses, and present strategies to leadership and investors. Collaborate cross-functionally and build vendor/alternative-data strategies to drive profitable growth while keeping losses within risk appetite.

Build, maintain, and optimize cloud data pipelines and dbt models; design Airflow DAGs; implement dimensional models and BI dashboards; integrate healthcare data with HIPAA-compliant practices; contribute to RAG pipelines and MLOps workflows; review contractor code, monitor data quality, and document designs following governance standards.

Maintain and ensure database accuracy, backups, security, and integrity. Develop and implement data standards and procedures, coordinate data collection, monitor compliance, troubleshoot data issues, and collaborate with IT to optimize data management.

Analyze datasets to generate reports and visualizations that inform business decisions. Produce regular reporting, create data visualizations, and work cross-functionally to support data-driven strategies with attention to accuracy.

Design, implement, and optimize Snowflake data storage and ETL solutions. Write and tune SQL, integrate data sources and BI tools, ensure data security and compliance, and collaborate with teams to meet business objectives.

Develop and maintain Python-based data applications and pipelines: fetch data from databases/APIs/files, build Pandas DataFrames/NumPy arrays, write complex SQL and data transformations, handle nested JSON, and collaborate with data science teams to deliver production data platforms.

Lead development and scaling of financial analytics: build data models, dashboards, and reporting; translate financial data into executive insights; embed predictive analytics; partner with Finance, IT, and business units to improve data quality, governance, forecasting, and automation.

Analyze business performance, provide insights, improve processes, participate in continuous improvement projects, and collaborate with cross-functional teams.