Top Remote Data & Analytics Jobs in Ann Arbor, MI

Support to evaluate and implement scalable data infrastructure. Work with technical teams to optimize data delivery and build reliable data systems. Expertise in data modeling, integration patterns, and data quality assurance is essential.

The Data Ingestion Specialist will manage the ingestion of healthcare data, improve data models, debug issues, and collaborate with team members to maintain pipeline reliability and efficiency.

Owner of data platform modernization: design and migrate legacy systems to Kimball-style dimensional models and star schemas; build reliable production data pipelines; enforce data hygiene and validation; champion dbt best practices; mentor junior engineers; collaborate with analysts and stakeholders to ensure scalable, well-documented data models and platform observability.

The Digital Analytics Analyst will develop data strategies, implement analytics tools, and translate complex data into actionable insights for business impact.

Collect and analyze competitive intelligence and conduct due diligence and investigations on investment candidates and related entities. Design data collection methods, use research, network analysis and AI/automation tools to produce high-quality reports and actionable recommendations for senior stakeholders, and improve workflow productivity.

Lead marketing analytics and root-cause investigations across the B2B SaaS funnel. Maintain data integrity and dashboards, monitor integrations (Marketo, Salesforce, 6Sense, Snowflake), quantify impact of trends, and recommend corrective actions. Architect and train AI/agent-driven analytics (Ask Anything), build semantic layers in Sigma/Snowflake, validate agent outputs, and partner with Revenue Marketing and Strategy teams to drive data-backed decisions and mentor junior analysts.

Lead the Statistical Programming team at Natera, overseeing programming activities for clinical validation in oncology, regulatory submissions, and developing programming infrastructure. Mentor team members and ensure high-quality analysis aligned with regulatory standards.

Design, build, and maintain scalable ETL/ELT pipelines and product-level data architectures. Improve pipeline performance and data freshness, lead code/design reviews, mentor engineers, and collaborate with Data Science, Product, and Engineering to make data reliable and accessible.

Lead end-to-end data conversion projects: analyze and profile legacy data, develop mappings and ETL/ELT transformations, validate and load data, resolve quality issues, coordinate cutovers, mentor juniors, and leverage generative AI to accelerate delivery.

Perform cross-product credit analytics to inform underwriting, limits, and portfolio strategy. Build customer credit profiles, run experiments (A/B tests), uncover insights, recommend and execute policy changes, and communicate results to leadership. Leverage internal and external data, predictive techniques, and AI tools to optimize approvals, risk, and product performance while balancing growth and loss.