Top Remote Analysis Reporting Jobs in Lincoln, NE

The Biostatistician designs, analyzes, and interprets clinical trial data, collaborating with various teams and ensuring statistical rigor and compliance with regulatory standards.

The Senior Product & Growth Analyst will lead the analytics behind Trust & Will's growth, focusing on conversion, retention, and lifetime value analysis. Responsibilities include building predictive models, conducting experimentation, and delivering data-driven recommendations to stakeholders. The role involves collaborating across product, marketing, and growth teams, with a strong emphasis on user behavior and funnel analysis.

Investigate financial transactions to identify potential money laundering activities, utilize AI for analysis, document findings, and collaborate with product teams on improvements.

As a Lead Data Engineer, you'll optimize data workflows, manage data engineering projects, mentor junior engineers, and ensure robust data solutions meet business needs.

The Data Engineer is responsible for developing data infrastructure, building data pipelines, managing data quality, and integrating analytics tools to support design and project operations.

Lead the design of DataOps platforms, focusing on scalable data infrastructures and automation frameworks. Oversee robust data orchestration and establish quality frameworks.

The role involves developing forecast models for oncology products, collaborating with teams, and communicating assumptions for strategic decision-making across the organization.

The BI Data Analyst III will provide insights for business decisions at Credible, focusing on the Insurance team. Responsibilities include developing dashboards, conducting data analysis, and collaborating across teams.

Design, develop, and maintain Power BI semantic models, dashboards, paginated and SSRS reports. Build DAX, Power Query transformations, ETL processes (SSIS/Azure Data Factory), and semantic/tabular models. Engage stakeholders, perform testing/UAT, document solutions, tune performance, and support multiple client engagements in a consulting environment.

Design, build, and automate scalable batch and streaming data pipelines, implement data models and ETL, automate deployments, support ML/experimentation, maintain server architecture, and partner with stakeholders to deliver analytics and data-driven tools.