Top Remote Analysis Reporting Jobs in Ann Arbor, MI

The Data Engineer will build real-time data pipelines for pricing algorithms, collaborate with teams, and contribute to batch data workflows.

The Senior Data Engineer will design and implement scalable data models in BigQuery using dbt for analytics and reporting, ensuring data governance and optimal performance.

The Director, Research - Power Markets is responsible for leading the QA/QC process for long-term forecasting, advising leadership, and ensuring market insights are effectively integrated into forecasts.

Lead client-facing data solutioning and pre-sales efforts for Consumer verticals, design executable data architectures, support pursuit to close, and provide ~50% hands-on delivery and architectural oversight while ensuring information security and data privacy compliance.

As a Staff Product Analyst, you'll define analytics strategies, build measurement infrastructure, design experiments, and partner with product teams to boost self-serve conversion and product adoption.

The Senior Consumer Insights Analyst leads consumer insights within cross-functional teams by managing research processes, synthesizing data, and delivering actionable findings to influence product development and strategy.

As a Staff Data Analyst, you'll drive data analysis, build business intelligence tools, and collaborate across teams to optimize Upstart's servicing strategy, while mentoring junior analysts.

The Staff Analytics Engineer will own the Financial Subledger Data Platform, build dbt models, implement data quality controls, and mentor a junior engineer, ensuring high operational reliability and cross-functional collaboration.

The Principal Data Platform Engineer leads the design of data architectures, implements data platform patterns, and optimizes system performance, ensuring data strategy operates at scale.

Lead and scale reporting and analytics in a fast-paced environment, managing a US and India-based team while delivering insights and resolving bottlenecks across data workflows.

Design and build data warehouse architecture, develop ETL/ELT pipelines, implement data governance, and partner with teams to improve data systems.