Top Analysis Reporting Jobs in Detroit, MI

Design, build, and maintain scalable ETL/ELT data pipelines and analytical platforms on AWS and Databricks. Migrate legacy workflows to cloud-native services, implement data lake and catalog solutions, enable AI/RAG/vector search, ensure FedRAMP/NIST compliance, optimize performance, and mentor junior engineers while collaborating in Agile teams.

The role involves leading global forecasting and performance management, setting standards, overseeing processes, collaborating with cross-functional teams, and developing a high-performing team in the oncology biotech sector.

Lead analytical efforts in Real World Data research, develop specifications and methodologies, manage projects, and communicate findings to stakeholders.

The Business Intelligence / Data Analyst will optimize the data reporting pipeline using Google Big Query and Omni, work with product management, implement reports, and conduct ongoing maintenance.

As an Analytics Lead, you will manage the measurement strategy, oversee tracking architecture, design testing frameworks, and create insights for clients. You'll lead a junior specialist and ensure data integrity across client accounts. Responsibilities include building dashboards, interpreting metrics, and creating measurement plans to drive business decisions.

The Sr. FWA Analyst identifies fraud, waste, and abuse in medical billing through data analysis, supporting engineering and data science teams with validation and tuning of detection algorithms.

Lead Oracle Cloud reporting initiatives, ensuring data accuracy and performance while mentoring junior analysts and collaborating with stakeholders.

The Data Analyst will build key data models and metrics for decision-making, partner with stakeholders for analytical insights, create datasets for self-service reporting, and ensure data reliability through quality checks.

Lead administration and optimization of the Snowflake data warehouse. Design and enforce data management and security policies, tune performance and costs, lead migrations and ETL initiatives, manage Snowflake roles/SSO, mentor DBAs, and maintain architecture documentation while collaborating with data engineers and analysts.

Design and run evaluation frameworks to assess third-party vendor data for fraud detection. Build lift analyses, backtests, and champion/challenger tests; profile vendor datasets for quality and coverage; collaborate with fraud, product, and data engineering to define ingestion and testing requirements; translate findings into actionable recommendations and maintain an internal knowledge base; support ad hoc analyses on fraud trends and model performance.