Top Data & Analytics Jobs in Ann Arbor, MI

As a Data Analyst at Wellthy, you will analyze data, create reports, and integrate AI tools to improve efficiency in data workflows and decision-making.

The Senior Data Engineer will design and maintain data infrastructures, support analytics, and collaborate with stakeholders to improve data quality and governance while utilizing DBT and AWS tools.

The Senior Data Analyst will lead complex data analysis projects, mentor junior analysts, develop dashboards, and provide insights to drive strategic decisions. Responsibilities include troubleshooting data issues and communicating findings effectively.

The Senior Product Analyst role involves data analysis, A/B testing, generating insights, and collaborating cross-functionally to enhance product strategies.

The Data Engineer will design and maintain data pipelines, optimize cloud data warehouses, and collaborate with analytics teams while mentoring junior staff.

The QA Analyst is responsible for ensuring product excellence through user requirement testing, defect management, and automation of software workflows. They create test cases, prioritize execution, conduct exploratory testing, and work closely with QA engineers to enhance automation coverage.

As a Jr. Sales Commission Analyst, you will calculate commission payments, prepare statements, resolve discrepancies, and ensure compliance with SOX controls while maintaining data accuracy.

Design, develop, and manage data infrastructure for internal and client projects, focusing on large-scale data pipelines, APIs, and cloud deployments.

Entefy seeks a Senior Data Scientist with a Master's or PhD in a relevant field, and 3+ years of experience. Responsibilities include delivering advanced analytics, leading teams, and extracting insights from datasets.

Serve as an AI/ML-focused solution engineer for Healthcare & Life Sciences: provide technical guidance, design cloud data and lakehouse architectures on Snowflake, lead demos and proofs-of-concept, support sales cycles, collaborate with product and engineering, and communicate AI/ML value to technical and executive stakeholders.